Vision of Autonomous Ride-sharing in 2030
The project focuses on human factors and aims to improve the ride-sharing experience. It discusses human engagement in the High Automation era and opportunities to design visual feedbacks to reduce human cognitive workload, bring enjoyment, and support future intelligent transportation systems.
Human Engagement in High Automation Stage
Automation is not "all-or-none"
- Lack of human engagement affects their performance
Factors: Mental underload, low situational awareness (SA), trust (mistrust, distrust, and overtrust) and cognitive skill degradation
- "In and out of the loop" safety
Car designers should resist high automation of action selection in order to maintain passenger's situation awareness so people can smoothly “re-enter the loop".
- Customization of multi-modal feedbacks
The needs of novice and expert or that of different age groups differ; other reasons include accessibility and possible sensory narrowing caused by the conflict when inter-modal overload occurs.
Inspiration from Model Adaptive Reference Control (MARC)
The system should allow passengers to interfere the computer's decisions with new "parameters" at any time and that will influence the outcome but the whole system still maintains a high level of automation.
Subjective experience is enhanced by allowing passengers to improvise.
User journey: short trip at midday
3D mapping projection as display
High-field electroluminescence functions with the display of the system’s executions that can be applied when:
Route changes;Destination is close/unavailable; New passenger arrives
Better Integration, better communication.
From Simple to Comprehensive
Customizable information of resources in the city;
Age- and/or Expertise Specific Modes;
Predictable Signal Location
Multiple / Group
Facilitation for individual