%0 Journal Article
%T 基于最优计算量分配的公路轨迹规划<br>On-road trajectory planning based on optimal computing budget allocation
%A 付骁鑫
%A 江永亨
%A 黄德先
%A 王京春
%A 黄开胜
%J 清华大学学报（自然科学版）
%D 2016
%R 10.16511/j.cnki.qhdxxb.2016.21.024
%X 针对智能汽车的公路轨迹规划问题, 本文将最优计算量分配(OCBA)的思想引入基于候选轨迹曲线的规划算法OODE, 提出新算法OCBA_OODE。OODE通过比较各候选曲线的"粗糙"(存在偏差但计算量小)评价确定最优轨迹曲线。曲线评价随着投入计算量的增加逐渐收敛至准确值, OODE对各曲线平均分配计算量, OCBA_OODE基于曲线评价循环分配计算量进而提高算法效率。OCBA_OODE在求解质量不下降的前提下, 规划速度比OODE的快20%。<br>Abstract：This paper presents an algorithm named OCBA_OODE for on-road trajectory planning by using optimal computing budget allocation (OCBA) in a candidate-curve-based planning algorithm named OODE. OODE picks the best trajectory by comparing rough (biased but computationally inexpensive) evaluations of a set of candidate curves. The curve evaluation converges to the real value as the computing budget increases. OODE allocates the equal parts of the computing budget to each curve, while OCBA_OODE repeatedly allocates the budget according to the latest curve evaluations to improve the planning efficiency. OCBA_OODE is 20% faster than OODE while maintaining the same solution quality.
%K 最优计算量分配
%K 轨迹规划
%K 智能汽车
%K 序优化
%K &lt
%K br&gt
%K optimal computing budget allocation
%K trajectory planning
%K intelligent vehicles
%K ordinal optimization
%U http://jst.tsinghuajournals.com/CN/Y2016/V56/I3/273