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In order to explore the heterogeneity sources of the influencing factors of traffic accident severity on low-grade highway and analyze the causal mechanisms of accident severity, based on traffic accident records of a low-grade highway in Chongqing city in the past 7 years, combined with the classification of collision vehicle types, the accident severity inducement analysis model was constructed using the fixed parameter Logit, mixed Logit, and random parameter Logit models considering heterogeneity sources. The differences in goodness-of-fit and heterogeneity of different models were analyzed, and the influence of significant variables on accident severity was quantified using average elasticity coefficient. The results show that the Logit model with random parameters considering heterogeneous sources has the highest goodness-of-fit under the same type of accident conditions. In the comprehensive accident model, the non-motor vehicle of the involved party has the greatest influence on the accident severity. The frontal collision is a heterogeneous variable that obeys a normal distribution of (-0.668, 0.7492). The mean and variance of the parameters are positively influenced by summer and large accident-causing vehicles. The season and involved vehicle types exhibit the largest effect intensity in the vehicle-to-vehicle accident model. The parameters associated with summer, mid-sized accident-causing vehicles, and side collisions follow a one-sided triangular distribution with mean (variance) of 0.586, 0.948, and 0.631, and have mean heterogeneity with the factors of night and horizontal curve radius greater than 1 600 m. The severity of vehicle-to-non-motor vehicle accidents is significantly affected by the variables of non-motor vehicle, night, and frontal collision. The parameters corresponding to the night and involved non-motor vehicle variables obey the unilateral triangular distribution of the mean (variance) 2.040 and 1.330, the mean value of parameters is significantly correlated with the weekend and age over 59 years old. Reasonably segmenting the accident dataset of low-grade highways in mountainous areas helps to reduce the heterogeneity effect in the factors affecting accident severity and improve the accuracy and reliability of accident severity cause analysis results.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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