An In-Depth Investigation Of Vehicle-Pedestrian Impact Accidents And Injury Epidemiology

Today, China is the country with the largest number of traffic fatalities every year, and pedestrians account for the vast majority of these fatalities. Each year in China, about 23,000 pedestrians die in traffic accidents, which accounts for 26% of the total traffic fatalities. Moreover, most pedestrian casualties were young adults–often the breadwinners in the family. Therefore, economic losses and psychological damage resulting from traffic injuries have significant negative impact on economic development and social stability. Consequently, the research of pedestrian safety has a broad practical significance and social value. However, it began relatively late in China, especially for basic and applied research, such as in-depth pedestrian accident analysis and injury epidemiology research, there is still a wide gap in comparison to the research level overseas. In short it is important to perform pedestrian accident analysis and carry out the research of injury epidemiology in order to reduce casualties and improve pedestrian safety in China.This paper aims to examine the principles of pedestrian accidents, find the causes and the types of pedestrian injuries; study the quantitative function relationship between accident factors such as impact speed and pedestrian injury risk based on the Logistic regression analyses and data mining technique through the in-depth pedestrian accident analysis and the research of injury epidemiology; predict and evaluate the protective effectiveness of vehicle active safety devices. The results of the analysis can be used to improve the automobile safety design and develop pedestrian injury protective systems.A special team from the research centre of vehicle and traffic safety of Hunan University carried out an in-depth investigation of vehicle traffic accident in Changsha. This team consisted of researchers from the university as well as medical and traffic authority sectors. The vehicle accident data were collected from the Traffic Police Bureau and hospitals from 2001 to 2008. The collected cases were analyzed with detailed information from the police, hospital, and retrospective investigations, as well as from on-site investigations. Through this investigation a vehicle accident database was developed, which called the In-depth Investigation of Vehicle Traffic Accident in Changsha (IVAC). All of these collected cases were documented in the database. The data of this research project came from the IVAC pedestrian database. The main research contents and results are as follows:Firstly, based on the 518 IVAC pedestrian accident cases, in-depth accident statistical analyses and injury epidemiology analyses were carried out with various analysis methods, including descriptive statistics, circle distribution and years of potential life lost analysis etc. Moreover, data mining for pedestrian fatality cases was conducted with the Bayesian network method. The results from these analyses indicated that the main characteristics of the accidents were the following: The distribution of pedestrian accidents in 12 month and 24-hour periods showed the focus trends; The two most common scenarios (F1 and F2) were identified as the pedestrian crossing a straight road from the left (F1) or the right; traffic control services were inadequate, and more than one-third of the accident sites were without traffic control measures; more than 80% of accident vehicles were passenger cars; the head and lower extremities were the body parts with high injury risks; as injury severity increased, the proportion of men and women also increased to 2:1; the age group of 41-45 years had a higher incidence of accidents than other age groups; average potential life lost of a pedestrian death was 33.7 years, which was far higher than some of the consequences of malignant disease; the research of Bayesian network model based on pedestrian fatalities indicated that the vehicle travel speed was the most important factor in affecting death risk of pedestrian.Secondly, the association between the impact speed and risk of pedestrian casualties in passenger vehicle collisions was investigated. According to the sampling criteria the data set was selected from IVAC database, which included 104 pedestrian accident cases, and was weighted based on the national traffic accident data. The logistical regression models of the risks for pedestrian fatalities and AIS 3+ injuries were developed in terms of vehicle impact speeds using the unweighted and weighted data sets. A multiple logistic regression model on the risk of pedestrian AIS 3+ injury was developed with consideration of age and impact speeds as two variables. It was found that impact speeds were significantly related to the risk of death and AIS3 + injury. The results demonstrated that the risk of pedestrian AIS3+ injury was approximately 50% at an impact speed of 51 km/h, and the risk of pedestrian fatality was approximately 50% at an impact speed of 58 km/h. At an impact speed of 80 km/h, the pedestrian rarely survives. The weighted risk curves indicated that the risks of pedestrian fatality and injury in China were higher than that in other high-income countries, whereas the risks of pedestrian casualty was lower than in these countries 30 years ago. Thirdly, car-pedestrian accident scenarios were analyzed using 389 pedestrian cases selected from the IVAC database. A mathematical model was developed with the frontal impact cases of the most common F1 or F2 scenario accidents. The following four parameters describing the configuration before the accident event were studied: the trajectory and speed for both the car and the pedestrian. Considering the different half detective angles of the sensor system (15 degree, 30 degree, 45 degree), the probabilities of pedestrian detection were calculated. It was found that when the half detective angle was equal or larger than 30 degrees the sensor system could detect more than 90% of the pedestrians in both evaluated scenarios.Finally, based on the 83 IVAC pedestrian cases the effectiveness of automatic braking systems was calculated for reducing the risks of pedestrian fatalities and severe injuries. The impact of sensor detection angles (60°,180°) and action times (0.5s,1s) of automatic braking systems were considered. The study documents that the effectiveness of reducing fatal injuries of pedestrians reached 86.8% at a field of view of 60°and braking 1s before the collision.In summary, this paper focused on the in-depth pedestrian accident analyses, and the quantitative analyses of injury risks. Moreover predictive research on the probability and effectiveness of active safety systems at reducing pedestrian injury risk were carried out based on real accident cases. The results from these studies provided valuable background knowledge for development of pedestrian injury protection systems.