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Suppose Future Traffic Accidents Based on Development of Self-driving Vehicles

机译:假设基于自动驾驶汽车的发展的未来交通事故

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With the development of self-driving vehicles, the future road traffic system will be dramatically changed, and so will be the characteristics of road traffic accidents. It is necessary to keep abreast of the dynamic development of the vehicle models to grasp the trend of the accident forms. Based on Human-Machine-Environment System Engineering theory, after study and analysis of the development trend of self-driving vehicles, considering the changes in all kinds of factors, such as human, vehicle, and road, this article supposes the new forms of road accidents that may occur in future. Due to the uneven development, there might be vehicles of different intelligence levels co-existing and influencing each other, which, together with the complexity of existing human, vehicle, and road factors, may cause even more complex traffic accident forms. New traffic phenomena in future, such as the coexistence of various self-driving vehicles and human-driving vehicles, switching between human-driving and self-driving, information security of intelligent transportation systems, and environmental interference and adverse weather factors, may cause accidents. Among them, the human factor is still important and should not be overlooked. The collision avoidance of self-driving vehicles should focus on the vulnerable road users. The study analyzes and forecasts the possible complexity of the future accidents, and suggests that in future the characteristics of accidents form change should be revealed in depth, so as to work out plans for preventing and handling the related accidents.
机译:随着自动驾驶汽车的发展,未来的道路交通系统将发生巨大变化,道路交通事故的特征也将随之改变。必须及时了解车辆模型的动态发展,以掌握事故形式的趋势。本文基于人机环境系统工程理论,在研究分析了自动驾驶汽车的发展趋势之后,考虑了人,车,路等各种因素的变化,提出了自动驾驶汽车的新形式。将来可能发生的道路交通事故。由于发展不平衡,可能会存在不同智能水平的车辆并存并相互影响,再加上现有的人,车和道路因素的复杂性,可能导致更为复杂的交通事故形式。未来新的交通现象,例如各种自动驾驶汽车和自动驾驶汽车的共存,自动驾驶和自动驾驶之间的切换,智能交通系统的信息安全以及环境干扰和不利的天气因素等,可能会导致事故的发生。 。其中,人为因素仍然很重要,不容忽视。避免自动驾驶汽车的碰撞应着眼于易受伤害的道路使用者。该研究分析并预测了未来事故可能发生的复杂性,并建议未来应进一步揭示事故形式变化的特征,从而制定预防和处理相关事故的计划。

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