activity
20182021
most citedExplicit behaviors affected by driver's trust in a driving automation system

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention

Hao Cheng, Li Feng, Hailong Liu +3

Intersections where vehicles are permitted to turn and interact with vulnerable road users (VRUs) like pedestrians and cyclists are among some of the most challenging locations for…

cs.HC2021

Autonomous Vehicles Drive into Shared Spaces: eHMI Design Concept Focusing on Vulnerable Road Users

Yang Li, Hao Cheng, Zhe Zeng +2

In comparison to conventional traffic designs, shared spaces promote a more pleasant urban environment with slower motorized movement, smoother traffic, and less congestion. In the…

cs.HC2020

What Timing for an Automated Vehicle to Make Pedestrians Understand Its Driving Intentions for Improving Their Perception of Safety?

Hailong Liu, Takatsugu Hirayama, Luis Yoichi Morales +1

Although automated driving systems have been used frequently, they are still unpopular in society. To increase the popularity of automated vehicles (AVs), assisting pedestrians to…

cs.HC20191 cited

Explicit behaviors affected by driver's trust in a driving automation system

Hailong Liu, Toshihiro Hiraoka, Seiya Tanaka

As various driving automation system (DAS) are commonly used in the vehicle, the over-trust in the DAS may put the driver in the risk. In order to prevent the over-trust while driv…

cs.HC2018

Driving behavior model considering driver's over-trust in driving automation system

Hailong Liu, Toshihiro Hiraoka

Levels one to three of driving automation systems~(DAS) are spreading fast. However, as the DAS functions become more and more sophisticated, not only the driver's driving skills w…