Peek into the Future Camera-based Occupant Sensing in Configurable Cabins for Autonomous Vehicles
Avinash Prabu, Renran Tian, Lingxi Li, Jialiang Le, Srinivasan, Sundararajan, Saeed Barbat

TL;DR
This paper explores camera-based occupant sensing in autonomous vehicle cabins with configurable seats, using simulation to optimize camera placement for full or partial occupant coverage despite occlusion challenges.
Contribution
It introduces a simulation-based framework to optimize camera placement for occupant coverage in flexible vehicle cabins, addressing occlusion issues in visual sensing systems.
Findings
Optimal camera layouts depend on seat configurations.
Up to six seats can be fully or partially covered with the proposed method.
Simulation results guide sensor placement for future autonomous vehicle designs.
Abstract
The development of fully autonomous vehicles (AVs) can potentially eliminate drivers and introduce unprecedented seating design. However, highly flexible seat configurations may lead to occupants' unconventional poses and actions. Understanding occupant behaviors and prioritize safety features become eye-catching topics in the AV research frontier. Visual sensors have the advantages of cost-efficiency and high-fidelity imaging and become more widely applied for in-car sensing purposes. Occlusion is one big concern for this type of system in crowded car cabins. It is important but largely unknown about how a visual-sensing framework will look like to support 2-D and 3-D human pose tracking towards highly configurable seats. As one of the first studies to touch this topic, we peek into the future camera-based sensing framework via a simulation experiment. Constructed representative…
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