most citedWork with AI and Work for AI: Autonomous Vehicle Safety Drivers' Lived Experiences

19 citations · 30 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2023

What Makes a Fantastic Passenger-Car Driver in Urban Contexts?

Yueteng Yu, Zhijie Yi, Xinyu Yang +11

The accurate evaluation of the quality of driving behavior is crucial for optimizing and implementing autonomous driving technology in practice. However, there is no comprehensive…

cs.HC2023★ 19 cited

Work with AI and Work for AI: Autonomous Vehicle Safety Drivers' Lived Experiences

Mengdi Chu, Keyu Zong, Xin Shu +5

The development of Autonomous Vehicle (AV) has created a novel job, the safety driver, recruited from experienced drivers to supervise and operate AV in numerous driving missions.…

cs.HC2023

Annotating Covert Hazardous Driving Scenarios Online: Utilizing Drivers' Electroencephalography (EEG) Signals

Chen Zheng, Muxiao Zi, Wenjie Jiang +5

As autonomous driving systems prevail, it is becoming increasingly critical that the systems learn from databases containing fine-grained driving scenarios. Most databases currentl…

cs.HC2023★ 10 cited

Side-by-Side vs Face-to-Face: Evaluating Colocated Collaboration via a Transparent Wall-sized Display

Jiangtao Gong, Jingjing Sun, Mengdi Chu +7

Traditional wall-sized displays mostly only support side-by-side co-located collaboration, while transparent displays naturally support face-to-face interaction. Many previous work…

cs.AI2022★ 1 cited

Evaluation of Pedestrian Safety in a High-Fidelity Simulation Environment Framework

Lin Ma, Longrui Chen, Yan Zhang +9

Pedestrians' safety is a crucial factor in assessing autonomous driving scenarios. However, pedestrian safety evaluation is rarely considered by existing autonomous driving simulat…