Abstract
The race to commercialize self-driving vehicles is in high gear. As carmakers and tech companies focus on creating cameras and sensors with more nuanced capabilities to achieve maximal effectiveness, efficiency, and safety, an interesting paradox has arisen: the human factor has been dismissed. If fleets of autonomous vehicles are to enter our roadways they must overcome the challenges of scene perception and cognition and be able to understand and interact with us humans. This entails a capacity to deal with the spontaneous, rule breaking, emotional, and improvisatory characteristics of our behaviors. Essentially, machine intelligence must integrate content identification with context understanding. Bridging the gap between engineering and cognitive science, I argue for the importance of translating insights from human perception and cognition to autonomous vehicle perception R&D.
| Original language | English (US) |
|---|---|
| Article number | AVM-054 |
| Journal | IS and T International Symposium on Electronic Imaging Science and Technology |
| Volume | 2019 |
| Issue number | 15 |
| DOIs | |
| State | Published - Jan 13 2019 |
| Externally published | Yes |
| Event | 2019 Autonomous Vehicles and Machines Conference, AVM 2019 - Burlingame, United States Duration: Jan 13 2019 → Jan 17 2019 |
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Software
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics