An assisted driving method and system based on machine vision
By using multi-view vision sensors and spatiotemporal fusion technology, a three-dimensional scene representation model and a hierarchical environmental cognition map are constructed, generating a dynamic risk distribution heat map. A multi-objective optimization algorithm is used to generate a driving trajectory that balances safety, comfort, and efficiency, solving the problem of inaccurate environmental understanding in intelligent driving systems and achieving precise, flexible, and safe assisted driving.
Patent Information
- Authority / Receiving Office
- CN Β· China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN LEADER AUTOMOTIVE INTELLIGENT TECH DEV CO LTD
- Filing Date
- 2026-02-03
- Publication Date
- 2026-07-24
AI Technical Summary
Existing intelligent driving systems lack accurate understanding of the surrounding environment, resulting in poor assisted driving performance and even safety risks.
Multi-view image data is collected by an onboard multi-view vision sensor array to construct a raw visual dataset containing spatial coordinate information. Spatiotemporal fusion processing is then performed to establish a unified three-dimensional spatial coordinate system. Semantic features are extracted to construct a hierarchical environmental cognition map, and a dynamic risk distribution heat map is generated. A multi-objective optimization algorithm is used to generate candidate driving trajectories that take into account safety, comfort, and efficiency, and refined control commands are output.
It achieves more precise, flexible and safer assisted driving effects, improves the driving experience and driving safety, and avoids the problems of being overly conservative or overly aggressive in traditional methods.
Smart Images

Figure CN122009210B_ABST