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Multi-driver agent-based traffic simulation systems for evaluating the effects of advanced driver assistance systems on road traffic accidents

机译:基于多驾驶员代理的交通模拟系统,用于评估高级驾驶员辅助系统对道路交通事故的影响

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摘要

A recent investigation revealed that there is a substantiated need for the development of a micro-simulation system designed for traffic safety assessment. This paper describes the development of a road traffic simulation system, which uses a 'nanoscopic model' of driver behaviour and an integrated analysis-evaluation system designed for traffic safety assessment. The primary focus is on estimating the effects of an advanced driver assistance system thereby reducing traffic accidents. The effectiveness and validity of the present system are demonstrated through comparison with measured traffic data. This paper also proposes algorithms embedded in a 'driver-agent', for recognising driver's intentions regarding choosing steering-control modes, lateral control tasks, and the driving mood. This is because the driver assistance systems need to recognise the driver's intention when choosing steering-control. The results of a simulation study, using the data drawn from actual driving, show that the systems would achieve a high recognition capability. As an example of how driving mood recognition applies to driver assistance systems, an advanced steering system and the adaptability to the driver's mood, have also been presented.
机译:最近的一项调查表明,确实有必要开发一种设计用于交通安全评估的微仿真系统。本文描述了道路交通仿真系统的开发,该系统使用驾驶员行为的“纳米模型”和专为交通安全评估而设计的综合分析评估系统。主要重点是评估高级驾驶员辅助系统的效果,从而减少交通事故。通过与实测交通数据的比较,证明了本系统的有效性和有效性。本文还提出了嵌入在“驾驶员代理”中的算法,用于识别驾驶员在选择转向控制模式,横向控制任务和驾驶心情方面的意图。这是因为驾驶员辅助系统在选择转向控制时需要识别驾驶员的意图。使用来自实际驾驶的数据进行的仿真研究结果表明,该系统将具有很高的识别能力。作为驾驶情绪识别如何应用于驾驶员辅助系统的示例,还提出了先进的转向系统以及对驾驶员情绪的适应性。

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