Analysis of Driver Behavior in Mixed Autonomous and Non-autonomous Traffic Flows
Analysis of Driver Behavior in Mixed Autonomous and Non-autonomous Traffic Flows
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DOI：
10.1177/1071181322661305
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发表时间：
2022-09
期刊：
影响因子：
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通讯作者：
Jundi Liu;L. Boyle
中科院分区：
文献类型：
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作者：
Jundi Liu;L. Boyle
自动驾驶汽车有望改善未来交通系统的道路安全和效率。设计了驾驶模拟器研究，以识别驾驶风格以及人类驾驶员与其他自动驾驶汽车之间的配合。该研究捕捉了驾驶员在完全自动驾驶环境下在无信号交叉路口的跟随行为。参与者被要求在两种不同的速度条件下（30,40英里/小时）和两种不同的交通密度条件下（有或没有其他交通）进行一系列的动作（直过十字路口，左转和右转）。方差分析表明，当驾驶员以较高的速度行驶时，他们在左转机动中有明显更大的偏差（定义为两个轨迹之间的区域）。第一次车削加工比第二次车削加工的偏差更小。研究结果对未来混合自主和非自主交通流中驾驶员辅助引导系统的设计具有启示意义。
Autonomous vehicles are expected to improve road safety and efficiency in future transportation systems. A driving simulator study was designed to identify driving styles and the cooperation between human drivers and other AVs. The study captured driver’s following behavior in a fully autonomous driving environment at unsignalized intersections. Participants were asked to make a series of maneuvers (straight through intersection, left turn, and right turn) in two different speed conditions (30, 40 mph) and two different traffic density conditions (with or without other traffic). Analysis of Variance showed that drivers had a significantly larger deviation (defined as the area between two trajectories) during left turn maneuvers when they were traveling at higher speeds. Moreover, the first turning operation had smaller deviation than the second turning operation. The findings have implications for the design of driver-assistance guidance systems in future mixed autonomous and non-autonomous traffic flows.