检查影响驾驶员伤害严重程度的因素与超速相关的碰撞:跨驾驶员年龄组的比较研究
Chamroeun Se1, Thanapong Champahom2, Sajjakaj Jomnonkwao3
1Institute of Research and Development, Suranaree University of Technology, Nakhon Ratchasima, Thailand.
International journal of injury control and safety promotion
|January 8, 2024
概括
超速显著增加了所有年龄段的驾驶员死亡风险. 年轻司机在汽车中面临更高的风险,而老年司机在恶劣条件下和特定道路类型上更容易受到伤害.
科学领域:
- 道路交通安全问题 道路安全问题
- 交通工程是交通工程.
- 事故分析 事故分析
背景情况:
- 单车超速事故对驾驶员的安全构成重大威胁.
- 了解这些车祸中的特定年龄风险对于有针对性的干预至关重要.
研究的目的:
- 为了调查影响驾驶员伤害严重程度的因素在超速相关的碰撞.
- 为了在不同的驾驶员年龄组中比较这些因素.
主要方法:
- 从泰国 (2012-2017) 分析事故数据.
- 利用一个随机值随机参数等级有序试验模型.
主要成果:
- 年轻司机在乘用车或皮卡车中超速行驶时增加了死亡风险.
- 年长的司机在恶劣天气,平坦的中间道路以及晚上高峰时段高速行驶时面临死亡风险的增加.
- 年轻和老年司机都面临着在恶劣天气中缺乏护的道路段上升级的死亡风险.
结论:
- 超速是加剧所有年龄组撞车严重性的关键因素.
- 干预措施必须针对驾驶员行为和道路基础设施,以减少与超速有关的撞车严重程度.
- 年龄特定的脆弱性凸显了针对道路安全策略的需求.
相关概念视频
Sight Distance in a Vertical Curve
47
Sight distance on vertical curves is critical in roadway design. It ensures drivers can see far enough ahead to identify and respond to hazards effectively. This directly impacts safety, driver comfort, and the overall efficiency of the transportation network.Vertical curves are classified into crest and sag curves based on their geometry. For crest curves, sight distance is determined by the line of sight between a driver's eye and a small object on the road's surface. Design parameters for...
47
Aging
52
Aging is a complex biological phenomenon influenced by various processes that affect cellular and systemic functions. Several prominent theories attempt to explain its mechanisms, highlighting cellular limitations, oxidative damage, and hormonal changes as central factors in aging.
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
52
Hypothesis Test for Test of Independence
3.6K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
H0: The two variables (factors)...
3.6K
Factors Influencing Heart Rate
2.7K
The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
2.7K
Impulse
18.9K
According to Newton’s second law of motion, the rate of change of the momentum of an object is the net external force acting on it. The total change in momentum between two timepoints thus depends on both the external force acting on it and the time over which it acts. Describing this mathematically, the total change of an object’s motion is proportional to the force vector and the time over which it is applied. This product is called impulse.
Additionally, it can be shown that the...
Additionally, it can be shown that the...
18.9K
Determination of Expected Frequency
2.2K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.2K


