Eco-Transportation and Alternative Technologies, Center for Infrastructure-Based Safety Systems, Virginia Tech Transportation Institute, 3500 Transp. Research Plaza, Blacksburg, VA 24061, United States.
Center for Infrastructure-Based Safety Systems, Virginia Tech Transportation Institute, 3500 Transp. Research Plaza, Blacksburg, VA 24061, United States.
J Safety Res. 2020 Jun;73:283-295. doi: 10.1016/j.jsr.2020.03.013. Epub 2020 May 5.
This study explored how drivers adapt to inclement weather in terms of driving speed, situational awareness, and visibility as road surface conditions change from dry to slippery and visibility decreases. The proposed work mined existing data from the SHRP 2 NDS for drivers who were involved in weather-related crash and near-crash events. Baseline events were also mined to create related metadata necessary for behavioral comparisons.
Researchers attempted, to the greatest extent possible, to match non-adverse-weather driving scenarios that are similar to the crash and near-crash event for each driver. The ideal match scenario would be at a day prior to the crash during non-adverse weather conditions having the same driver, at the same time of day, with the same traffic level on the same road on which the crash or near-crash occurred. Once the matched scenarios have been identified, a detailed analysis will be performed to determine how a driver's behavior changed from normal driving to inclement-weather driving.
Data collected indicated that, irrespective of site location (i.e., state), most crashes and near-crashes occurred in rain, with only about 12% occurring in snowy conditions. Also, the number of near-crashes was almost double the number of crashes showing that many drivers were able to avoid a crash by executing an evasive maneuver such as braking or steering.
Most types of near crashes were rear-end and sideswipe avoidance epochs, as the drivers may have had a difficult time merging or trying to change lanes due to low visibility or traffic. Hard braking combined with swerving were the most commonly used evasive maneuvers, occurring when drivers did not adjust their speeds accordingly for specific situations. Practical applications: Results from this study are expected to be utilized to educate and guide drivers toward more confident and strategic driving behavior in adverse weather.
本研究探讨了驾驶员在道路表面状况从干燥变为湿滑且能见度降低时，如何根据驾驶速度、情境意识和能见度来适应恶劣天气。本研究从 SHRP 2 NDS 中挖掘现有的数据，这些数据来自于与天气相关的碰撞和近碰撞事件中的驾驶员。还挖掘了基线事件，以创建与行为比较相关的必要元数据。
研究人员尽可能尝试为每位驾驶员匹配非恶劣天气驾驶情况下与碰撞和近碰撞事件相似的情景。理想的匹配情景是在发生碰撞之前的一天，在非恶劣天气条件下，由相同的驾驶员在相同的时间、相同的交通量，在发生碰撞或近碰撞的同一条道路上行驶。一旦确定了匹配的情景，将进行详细分析，以确定驾驶员的行为从正常驾驶到恶劣天气驾驶的变化情况。
收集的数据表明，无论地点（即州）如何，大多数碰撞和近碰撞都发生在雨中，只有约 12%发生在雪天。此外，近碰撞的数量几乎是碰撞的两倍，这表明许多驾驶员通过执行躲避动作（如刹车或转向）避免了碰撞。
大多数类型的近碰撞是追尾和侧面碰撞避让时期，因为驾驶员可能由于能见度低或交通拥堵而难以合并或试图变道。急刹车与转向相结合是最常用的躲避动作，当驾驶员没有根据特定情况相应调整速度时，就会发生这种情况。实际应用：预计本研究的结果将用于教育和指导驾驶员在恶劣天气下采取更自信和更具策略性的驾驶行为。
