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Target Selection Algorithm Based on Road Model and Scene Judgment
WANG Huanjie, LI Zijian, LI Youhao, YAO Lang, ZHAN Qi
2025, 50(2):
41-46.
DOI: 10.16638/j.cnki.1671-7988.2025.002.008
To improve the accuracy of adaptive cruise control (ACC) target selection in scenarios
such as turning, lane missing, and ultra wide lanes, a target selection algorithm based on road models
and scene judgment is proposed. Establishing optimization problems through the Ceres optimization
library, fully considering factors such as self vehicle historical trajectory, target vehicle historical
trajectory, self vehicle steering wheel angle, vehicle speed, lane line, road edge, etc., and assigning
different weights to generate a self vehicle pre driving reference line that can be used as the basis for
ACC target screening. For different scenarios, using the self vehicle pre driving reference line as the
benchmark to establish risk zones, judging the relative position relationship between each target
location point and the danger zone through geometric relationships, determining it as a following
target, entering and exiting the target, responding as soon as possible, and improving driving
experience and safety.
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