10 citations · 16 across the 5 of their papers we have counts for
5 papers
Adaptive Driving Style for SAE Level-2 Driving Automation: Minimizing Preference Mismatch
Kumar Akash, Zhaobo Zheng, Teruhisa Misu +4
Driving style is a key factor in the comfort and acceptance of automated vehicle (AV) features. In SAE Level-2 automation, where the driver must supervise the system and remain rea…
DualTake: Predicting Takeovers across Mobilities for Future Personalized Mobility Services
Zhaobo Zheng, Kumar Akash, Teruhisa Misu
A hybrid society is expected to emerge in the near future, with different mobilities interacting together, including cars, micro-mobilities, pedestrians, and robots. People may uti…
Beyond Empirical Windowing: An Attention-Based Approach for Trust Prediction in Autonomous Vehicles
Minxue Niu, Zhaobo Zheng, Kumar Akash +1
Humans' internal states play a key role in human-machine interaction, leading to the rise of human state estimation as a prominent field. Compared to swift state changes such as su…
Trust in Shared Automated Vehicles: Study on Two Mobility Platforms
Shashank Mehrotra, Jacob G Hunter, Matthew Konishi +6
The ever-increasing adoption of shared transportation modalities across the United States has the potential to fundamentally change the preferences and usage of different mobilitie…
Identification of Adaptive Driving Style Preference through Implicit Inputs in SAE L2 Vehicles
Zhaobo K. Zheng, Kumar Akash, Teruhisa Misu +4
A key factor to optimal acceptance and comfort of automated vehicle features is the driving style. Mismatches between the automated and the driver preferred driving styles can make…