Cooperative vehicle-infrastructure system (CVIS), one of the key development directions of intelligent transportation, can provide autonomous vehicles with perception information beyond the visual range through roadside sensors. Optimizing sensor placement is essential to use as few sensors as possible while meeting coverage requirements. This paper establishes the coverage model of roadside sensors (including cameras, millimetre wave radars and lidars), proposes an optimization method for roadside sensor placement, and applies it to real road scenes. Firstly, the relationship between roadside sensors' placement and coverage area is modeled according to the perceived characteristics and mounting parameters of different sensors. Then, this paper develops an optimization model for sensors placement based on the location relationship between different sensors, and employs a multi-objective Grey Wolf algorithm to solve the model. Finally, a method for optimal placement of roadside sensors using this optimization model was applied to a road section in the urban. The results show that the proposed method can use fewer sensors under the premise of satisfying the use effect, thereby saving costs and reducing energy consumption. This research contributes to realizing roadside sensors placement with high perceptual quality and developing autonomous driving.
Optimization of Roadside Sensors Placement for Cooperative Vehicle-Infrastructure System
2023-09-24
785684 byte
Conference paper
Electronic Resource
English