Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach
This work addresses the cost and design challenges of LiDAR implementation for autonomous vehicle manufacturers, offering an incremental improvement in sensor placement optimization.
The paper tackles the problem of optimally placing LiDAR sensors on autonomous vehicles to maximize utility by minimizing non-detectable areas, proposing a volume-to-surface-area ratio (VSR) measure and using an Artificial Bee Colony algorithm to find cost-effective configurations.
Autonomous vehicle manufacturers recognize that LiDAR provides accurate 3D views and precise distance measures under highly uncertain driving conditions. Its practical implementation, however, remains costly. This paper investigates the optimal LiDAR configuration problem to achieve utility maximization. We use the perception area and non-detectable subspace to construct the design procedure as solving a min-max optimization problem and propose a bio-inspired measure -- volume to surface area ratio (VSR) -- as an easy-to-evaluate cost function representing the notion of the size of the non-detectable subspaces of a given configuration. We then adopt a cuboid-based approach to show that the proposed VSR-based measure is a well-suited proxy for object detection rate. It is found that the Artificial Bee Colony evolutionary algorithm yields a tractable cost function computation. Our experiments highlight the effectiveness of our proposed VSR measure in terms of cost-effectiveness configuration as well as providing insightful analyses that can improve the design of AV systems.