Energy field-based lane changing behavior interaction model and risk evaluation in the weaving section of expressway.

OBJECTIVE: With the development of intelligent driving assistance systems, the evaluation of driving behavior risk has shifted from traditional single-vehicle studies to multi-vehicle studies. This study aimed to investigate the interaction mechanism between vehicles and to study the microscopic laws of traffic flow operation. METHODS: Firstly, the concept of "driving interaction field" was proposed. The virtual interaction quality and distance were used to define the driving interaction field. The interaction angle distinguished the vehicle interaction between different lanes. Then, the risk mechanism in the interaction process was analyzed by driving risk index. Corresponding thresholds of 50% and 85% quantile values were determined. Finally, the process of the lane-changing simulation experiments was divided into three phases (preparation, execution and adjustment). RESULTS: The driving risk index of the execution phase was larger than the other phases. Meanwhile, the comparison with the classical driving risk indexes revealed that the proposed index was more accurate and intuitive in describing the interaction risks. CONCLUSIONS: The driving interaction model proposed in this study quantified the overall environmental pressure on the vehicle. It overcomes the previous limitation of kinetic interaction parameters. The research provides a new idea for the ITS and autonomous driving systems, contributing to the enhancement of traffic safety and efficiency.

Comparison of the clinical characteristics in parents and their children in a series of family clustered Mycoplasma pneumoniae infections.

BACKGROUND: Mycoplasma pneumoniae infections have increased in China recently, causing some evidence of familial clustering. The purpose of this study was to compare the clinical features of parents and children in cases of familial clustering of Mycoplasma pneumoniae infection. METHODS: A retrospective analysis was performed on the cases of familial clustering of Mycoplasma pneumoniae infection, and the clinical characteristics of parents and children were compared. RESULTS: We identified 63 families, of these, 57 (65.5%) adults and 65 (94.2%) children required hospitalization. Fifty-seven adults (mean age 35.1 ± 4.6 years, 80.7% female) and 55 children (mean age 6.3 ± 3.9 years, 54.5% female) were included in the analysis. The incidence of mycoplasma infection in adults had increased gradually over the past year, while the rate in children had spiked sharply since June 2023. The clinical symptoms were similar in the two groups, mainly fever and cough. The peak temperature of children was higher than that of adults (39.1 ± 0.7℃ vs 38.6 ± 0.7℃, p = 0.004). Elevated lactate dehydrogenase was more common in children than in adults (77.8% vs 11.3%, p < 0.001). Bronchial pneumonia and bilateral involvement were more common in children, while adults usually had unilateral involvement. Three (60%) adults and 21 (52.5%) children were macrolide-resistant Mycoplasma pneumoniae infected. Children were more likely to be co-infected (65.5% vs 22.8%, p < .001). Macrolides were used in most children and quinolones were used in most adults. Ten (18.2%) children were diagnosed with severe Mycoplasma pneumoniae pneumonia, whereas all adults had mild disease. Children had a significantly longer fever duration than adults ((5.6 ± 2.2) days vs (4.1 ± 2.2) days, p = 0.002). No patient required mechanical ventilation or died. CONCLUSIONS: Mycoplasma pneumoniae infection shows a familial clustering epidemic trend at the turn of summer and autumn, with different clinical characteristics between parents and children.