The problem with lidar placement is finding a lidar position that reduces the dead zone and improves the point cloud resolution. A lidar placement method is thus proposed for the multiple lidar system of autonomous vehicles to resolve this problem. With the introduction of the lidar occupancy grid, the problem is formulated as an optimization problem. A genetic algorithm is subsequently applied to solve the optimization problem. The experimental results using commercial lidars are subsequently presented to show the usefulness of the proposed method.

Sensors on autonomous vehicles have inherent physical constraints. To address these limitations, several studies have been conducted to enhance sensing capabilities by establishing wireless communication between infrastructure and autonomous vehicles. Various sensors are strategically positioned within the road infrastructure, providing essential sensory data to these vehicles. The primary challenge lies in sensor placement, as it necessitates identifying optimal locations that minimize blind spots while maximizing the sensor’s coverage area. Therefore, to solve this problem, a method for positioning multiple sensor systems in road infrastructure is proposed. By introducing a voxel grid, the problem is formulated as an optimization challenge, and a genetic algorithm is employed to find a solution. Experimental findings using lidar sensors are presented to demonstrate the efficacy of this proposed approach.