超越传统:通过贝叶斯和机器学习模型探索州际公路上的行人安全
Sheikh M Usman1, Asad J Khattak1
1Department of Civil & Environmental Engineering, The University of Tennessee, Knoxville, United States.
Journal of safety research
|September 10, 2025
概括
当行人受损时,越过道路或在未照明的道路上,行人高速公路撞车事故更严重. 改善照明和使用技术可以提高高速公路行人安全.
科学领域:
- 交通安全 交通安全
- 运输工程 运输工程
- 公共卫生 公共卫生
背景情况:
- 联邦法律禁止在高速公路上行人,但14-17%的美国行人撞车事故发生在州际公路上.
- 通过安全系统的方法检查州际行人撞车事故对于降低风险至关重要.
- 这项研究侧重于北卡罗来纳州高速公路上的行人撞车伤害严重程度.
研究的目的:
- 在州际公路上调查行人撞车伤害严重程度的相关性.
- 在高速公路撞车中分析行人行为,道路状况和车辆类型.
- 利用从2007年到2022年的全面事故数据.
主要方法:
- 采用频率主义和贝叶斯二进制逻辑模型.
- 利用随机森林机器学习算法进行可靠的估计.
- 分析了882个高速公路上的行人撞车观察结果.
主要成果:
- 农村 (47%) 的行人撞车比城市 (40%) 的高速公路更频繁.
- 与站在路上 (OR=2.40),跨越高速公路 (OR=1.645),酒精障碍 (OR=2.51) 和黑暗的未亮段 (OR=2.00) 相关的严重行人伤害风险更高.
结论:
- 对于高速公路行人安全,需要采取多层次的方法,与安全系统金字塔保持一致.
- 策略包括加强道路照明和在夜间实施变速限制.
- 交通运输技术可以提醒司机注意行人,从而提高安全性.
相关概念视频
Steps in Outbreak Investigation
494
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
494
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
286
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
286
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
292
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
292
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
243
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
243
Clearance Models: Noncompartmental Models
244
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
244
Mechanistic Models: Compartment Models in Individual and Population Analysis
250
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
250


