Human error is one of the leading causes of accidents. Distraction, fatigue, poor visibility, speeding, and other such errors made by drivers can cause accidents. With the rapid advancements in automation technologies, transportation planners have strived to use Intelligent Transportation Systems (ITS) to minimize human error. In this study, the effect of Autonomous Vehicles (AVs) on the number of potential conflicts at two unsignalized intersections is investigated by using a microsimulation model in PTV Vissim software. For human-driven cars, the factor that is considered for calibration is driver distraction mainly caused by reading or writing text messages on a cellphone while driving. This factor can be estimated using driving simulators. In this paper, five different scenarios were defined for simulation, in addition to the primary state, according to the different market penetration rates of AVs in Vissim. Safety assessment was performed by the Surrogate Safety Assessment Model (SSAM) using Time to Collision (TTC) and Deceleration Rate to Avoid Crashes (DRAC) indicators to determine the number of accidents. It was concluded that the presence of 100% of AVs could reduce the potential for accidents by up to 93%.

中文翻译：

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研究自动驾驶汽车和分心驾驶对无信号交叉口安全的同时影响

人为错误是导致事故的主要原因之一。驾驶员分心、疲劳、能见度低、超速和其他此类错误都可能导致事故。随着自动化技术的快速进步，交通规划者一直在努力使用智能交通系统 (ITS) 来最大程度地减少人为错误。在这项研究中，通过使用 PTV Vissim 软件中的微观仿真模型，研究了自动驾驶汽车 (AV) 对两个无信号交叉路口潜在冲突数量的影响。对于人类驾驶汽车，校准考虑的因素是驾驶员分心，主要是在驾驶时在手机上阅读或编写短信。这个因素可以使用驾驶模拟器来估计。在本文中，除了主要状态外，还定义了五种不同的模拟场景，根据 Vissim 中 AV 的不同市场渗透率。安全评估由替代安全评估模型 (SSAM) 使用碰撞时间 (TTC) 和避免碰撞的减速率 (DRAC) 指标进行，以确定事故数量。得出的结论是，100% 的自动驾驶汽车的存在可以将事故的可能性降低多达 93%。