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基于关联规则挖掘的网约车驾驶员攻击性驾驶行为的情绪影响

Influence of emotions on the aggressive driving behavior of online -car-hailing drivers based on association rule mining.

机构信息

Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing, China.

Jiangsu Province Collaborative Innovation Center of Modem Urban Traffic Technologies, Southeast University, Nanjing, China.

出版信息

Ergonomics. 2024 Oct;67(10):1391-1404. doi: 10.1080/00140139.2024.2324007. Epub 2024 Apr 13.

Abstract

Emotion is an important factor that can lead to the occurrence of aggressive driving. This paper proposes an association rule mining-based method for analysing contributing factors associated with aggressive driving behaviour among online car-hailing drivers. We collected drivers' emotion data in real time in a natural driving setting. The findings show that 29 of the top 50 association rules for aggressive driving are related to emotions, revealing a strong relationship between driver emotions and aggressive driving behaviour. The emotions of anger, surprised, happy and disgusted are frequently associated with aggressive driving behaviour. Negative emotions combined with other factors (for example, driving at high speeds and high acceleration rates and with no passengers in the vehicle) are more likely to lead to aggressive driving behaviour than negative emotions alone. The results of this study provide practical implications for the supervision and training of car-hailing drivers.

摘要

情绪是导致驾驶攻击性的重要因素。本文提出了一种基于关联规则挖掘的方法,用于分析网约车司机攻击性驾驶行为的相关影响因素。我们在自然驾驶环境中实时收集了驾驶员的情绪数据。研究结果表明,攻击性驾驶的前 50 条关联规则中有 29 条与情绪有关,这表明驾驶员情绪与攻击性驾驶行为之间存在很强的关系。愤怒、惊讶、高兴和厌恶等情绪与攻击性驾驶行为密切相关。与单独的消极情绪相比,消极情绪与其他因素(如高速行驶、高加速度和车内无乘客)相结合更容易导致攻击性驾驶行为。本研究结果为网约车司机的监管和培训提供了实践意义。

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