车头时距
临界性
流量(计算机网络)
度量(数据仓库)
计算机科学
工作(物理)
集合(抽象数据类型)
数据集
碰撞
交通冲突
交通生成模型
模拟
数据挖掘
运输工程
浮动车数据
工程类
实时计算
交通拥挤
人工智能
物理
机械工程
核物理学
程序设计语言
计算机安全
作者
Friedrich Kruber,Jonas Wurst,Samarjit Chakraborty,Michael Botsch
出处
期刊:Cornell University - arXiv
日期:2019-03-11
被引量:3
摘要
This work provides a comprehensive analysis on naturalistic driving behavior for highways based on the highD data set. Two thematic fields are considered. First, some macroscopic and microscopic traffic statistics are provided. These include the traffic flow rate and the traffic density, as well as velocity, acceleration and distance distributions. Additionally, the dependencies to each other are examined and compared to related work. The second part investigates the distributions of criticality measures. The Time-To-Collision, Time-Headway and a third measure, which couples both, are analyzed. These measures are also combined with other indicators. Scenarios, in which these measures reach a critical level, are separately discussed. The results are compared to related work as well. The two main contributions of this work can be stated as follows. First, the analysis on the criticality measures can be used to find suitable thresholds for rare traffic scenarios. Second, the statistics provided in this work can also be utilized for traffic modeling, for example in simulation environments.
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