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Modeling urban road risky driving behaviors in China with multi-agent microscopic traffic simulation

机译:基于多智能体微观交通仿真的中国城市道路危险驾驶行为建模

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摘要

Typical driving behaviors such as car-following and lane-changing can be described based on common concepts. But these behaviors could be different from driver to driver, from nation to nation due to different individual influencing factors (e.g. age, gender, driving age, mood) and situational influencing factors (e.g. weather, congestion, respect for law). Studies show that drivers who have higher level of “driving discourtesy” (i.e rudeness and aggressiveness) have higher probability of performing risky driving behaviors including traffic rule violations. In this paper, we propose a model named Driving Discourtesy Model (DDM). In this model, a new indicator is defined to measure the “driving discourtesy”. With a probability distribution method, we are able to estimate the probability of performing risky driving behaviors of each vehicle based on a vehicle's individual influencing factors and situational factors. A multi-agent traffic simulation is developed to test DDM. The experiment results show that risky driving behaviors including speeding, lane-changing for taking speed advantages and driving on hard shoulder can be simulated effectively using DDM.
机译:可以基于常见概念来描述典型的驾驶行为,例如跟车和变道。但是由于不同的个人影响因素(例如年龄,性别,驾驶年龄,情绪)和情境影响因素(例如天气,交通拥堵,对法律的尊重),这些行为可能因驾驶员而异,因国家而异。研究表明,具有较高“驾驶不礼貌”(即粗鲁和进取心)的驾驶员更有可能执行危险的驾驶行为,包括违反交通规则。在本文中,我们提出了一个名为“驾驶离散模型”(DDM)的模型。在该模型中,定义了一个新的指标来衡量“驾驶不礼貌”。利用概率分布方法,我们能够基于车辆的个体影响因素和情况因素来估计每辆车辆进行危险驾驶行为的可能性。开发了一种多代理流量模拟来测试DDM。实验结果表明,使用DDM可以有效地模拟危险的驾驶行为,包括超速,换道以发挥速度优势以及在坚硬的肩膀上驾驶。

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