Abstract This chapter proposes an integrated current and future safety situation analysis framework as general as possible, where we model not only sensing phases, but also control phases. In this framework, a speed estimation algorithm based on lidar data is used to distinguish two types of obstacles: static objects and moving objects. On the basis of the speeds and types of obstacles, we form obstacle tracks using only a single sensor, and after that a track fusion approach is used to yield accurate and robust global tracks. Furthermore, we use camera to detect lanes and obstacles in Regions of Interest (ROIs) generated by range sensors, such as vehicles and pedestrians. Finally, combining the lane structure with obstacle tracks, we can model the traffic environment and assess road situation at both the current and near future time.
The Framework of Intelligent Vehicles
2011-01-01
7 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Interactive Safety Analysis Framework of Autonomous Intelligent Vehicles
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