Abstract: With the rapid development of artificial intelligence and ubiquitous sensing technology, intelligent assisted driving systems based on multimodal data fusion processing are gradually entering households. The core of intelligent driving technology relies on advanced artificial intelligence and ubiquitous sensor technology to enhance or replace the perception, decision-making, and execution capabilities of drivers. Among them, real-time, accurate, and robust perception of the road environment is an important part of vehicle intelligence. This article introduces a vehicle platform that integrates multiple sensors for multimodal data collection, and provides basic point cloud data services for assisted intelligent driving by constructing high-precision point cloud maps. Different from the “post-fusion” strategy of multi-source data fusion, this article adopts the strategy of “pre-fusion” with time-space synchronized multi-source data. Based on completing the synchronization and calibration of multi-source sensor data, it provides intelligent driving vehicles with perception data that is consistent in time and space. At the level of map construction, this article achieves high-precision reconstruction of environmental point cloud maps by coupling with IMU and solid-state lidar, providing important technical support for the realization and further development of assisted intelligent driving.

Key words: intelligent driving, multimodal data, precise perception, environmental mapping