Estimating Driving Fatigue at a Plateau Area with Frequent and Rapid Altitude Change

Assessment of particulate matter inhalation during the trip process with the considerations of exercise load

A Particulate Matter (PM) inhalation model considering exercise load is established to evaluate the impact of PM on residents' travel health. The study chooses PM detectors to collect PM concentrations at the various transportation space, including walking, bicycle, bus, taxi, and subway. A multiple linear regression model revised by road greening is utilized to study the influence factors that have a potential impact on the PM concentration. The air inhalation model with the consideration of exercise load can be acquired by connecting the heart rate (HR) and individual characteristics. The PM_2.5 and PM₁₀ inhalation for a complete trip of traveler can be estimated using the proposed model based on air inhalation per time unit, travel time, and PM concentration. The analysis results using the experimental data in Xi'an indicate that PM concentrations in taxi carriage, bus carriage, and subway carriage are significantly different from those obtained from environmental monitoring stations. However, the difference is not significant in the locations of sidewalk, non-motorized lane, taxi station, bus station, subway concourse, and subway platform. PM concentration and humidity in background environment have a positive influence on the increase of PM concentration in transportation environment, while temperature and wind speed are negative. The mean values of air inhalation per time unit for male and female using each mode are in the range of 9.6-26.8 L/min and 9.8-27.8 L/min, respectively. Exposure time in non-motorized transportation has a large effect on PM inhalation of travelers, walking connections and waiting in motorized transportation are the main contributing states to PM inhalation of travelers. The results of the study can be used to predict travelers' PM inhalation in completed trips, and provide recommendations for travelers to choose a healthier mode.

Analysis on alteration of road traffic casualties in western China from multi-department data in recent decade

Background

Road traffic safety has considerably improved in China. However, the changes may differ in the economically backward and altitude higher western region. This study aims to investigate changes in the occurrence and severity of traffic casualties in western China and illuminate several key causal factors.

Materials and methods

Traffic accident data from the Annual Traffic Accident Statistics Report combined with population and vehicle data from the China Statistics Bureau between 2009 and 2019, were retrospectively analyzed. Traffic accident numbers, fatalities, human injury (HI), case fatality rates (CFR), mortality per 100,000 population (MRP), and mortality per 10,000 vehicles (MRV) were compared between the western and eastern regions. The HI, CFR, MRV, and MRP between the four groups based on the altitude of cities, below 500 meters, 500 to 1,500 meters, 1,500 to 3,000 meters, and over 3,000 meters, were compared using one-way analysis of variance. One hundred and seventy-eight cases of extremely serious traffic accidents were further analyzed in terms of accident occurrence time, vehicle type, road grade, road shape, accident pattern, and accident reason. The differences of accident characteristics between the eastern and western regions were compared using the chi-square test.

Results

The number of traffic accidents and fatalities decreased in low-altitude areas in western China. However, there was a significant increasing trend in the high altitude area. The HI, CFR, MRV, and MRP were higher in the western region than that in the eastern and national. Those accident indicators tended to increase with increasing altitude. And there were statistically significant differences (p < 0.05) among groups from different altitudes. Chi-square test results show that there are statistically significant differences (p < 0.05) in term of road grade, road shape, accident pattern between eastern and western. Low-grade roads, combined curved and sloping roads, and rollover were significant features associated with traffic accidents in the western region. Bad roads were the main cause of rollover accidents in western China, which will lead to more serious casualties. Over speeding, overloading, bad weather, vehicle failure, and driver error were the top five accident causes.

Conclusion

Traffic accidents are increasing in high-altitude areas of western China, and they lead to more severe casualties. The characteristics of serious traffic accidents in this part of the country differ from those of the eastern regions. Improving road safety facilities, restrictions of speed, and improving medical treatment at accident scenes may be effective measures to reduce traffic accidents related injuries in the western region.

Health risk assessment of PM2.5 on walking trips

PM_2.5 has an impact on residents' physical health during travelling, especially walking completely exposed to the environment. In order to obtain the specific impact of PM_2.5 on walking, 368 healthy volunteers were selected and they were grouped according to gender and age. In the experiment, the heart rate change rate (HR%) is taken as test variable. According to receiver operating characteristic (ROC) curve, the travel is divided into two states: safety and risk. Based on this, a binary logit model considering Body Mass Index (BMI) is established to determine the contribution of PM_2.5 concentration and body characteristics to travel risk. The experiment was conducted on Chang'an Middle Road in Xi'an City. The analysis results show that the threshold of HR% for safety and risk ranges from 31.1 to 40.1%, and that of PM_2.5 concentration ranges from 81 to 168 μg/m³. The probability of risk rises 5.8% and 11.4%, respectively, for every unit increase in PM_2.5 concentration and HR%. Under same conditions, the probability of risk for male is 76.8% of that for female. The probability of risk for youth is 67.5% of that for middle-aged people, and the probability of risk for people with BMI in healthy range is 72.1% of that for non-healthy range. The research evaluates risk characteristics of walking in particular polluted weather, which can improve residents' health level and provide suggestions for travel decision while walking.