发表机构
Clausthal University of Technology; Leibniz University Hannover（克劳斯塔尔工业大学; 莱布尼茨汉诺威大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
CLIPPER是用于重复空间覆盖规划的可重放优化方法，通过构建候选池等技术实现，在多地城市规模测试中，大幅降低了规划推出时间，覆盖度与全量贪心算法接近。
AI 中文摘要
不伦瑞克市制定的运营要求对市政 micromobility（微型移动）规划施加了地理围栏排除区、强制保留站点、间距规则及区域上限等限制。每次政策调整都需要生成新的可行规划；在城市规模下，全量贪心算法每次备选方案需耗时数十秒。我们提出CLIPPER（Constraint-exact Low-latency Iterative Planning with Pooled Evaluation and Replay，即带聚合评估与重放的约束精确低延迟迭代规划）。它构建有界候选池，但在选择前会重新计算当前精确收益并检查所有活跃约束。各候选单独的覆盖范围设定初始顺序；离线全量扫描测量候选池遗漏的收益；在线阶段，保守边界触发扩展或审计。CLIPPER-F为每个提案组分配相同数量的候选槽位。在不伦瑞克、慕尼黑和柏林三地，在相同政策下，其完整链的平均覆盖度与全量贪心算法的差距在0.245个百分点以内，平均推出时间降低13.6至28.9倍。CLIPPER-A则在各组间分配共享的候选预算。在其覆盖优先政策下，相同政策下的平均推出时间仅为全量贪心算法的9%至15%，在不伦瑞克的平均差距为1.82个百分点，慕尼黑为0.12个百分点，柏林为0.27个百分点。总体而言，CLIPPER可在强制执行所有编码模型约束的同时，实现对记录的城市规模规划状态的快速、可重放比较。
英文摘要
Operational requirements developed with the City of Braunschweig frame municipal micromobility planning under geofenced exclusions, mandatory retained sites, spacing rules, and area-level caps. Each policy edit requires a new feasible plan; full-set greedy takes tens of seconds per alternative at city scale. We present CLIPPER (Constraint-exact Low-latency Iterative Planning with Pooled Evaluation and Replay). It forms bounded candidate pools but recomputes exact current gains and checks every active constraint before selection. Coverage from each candidate alone sets the initial order. Offline full-set scans measure gains omitted by the pool; online, a conservative bound triggers expansion or audit. CLIPPER-F gives each proposal group the same number of candidate slots. Across Braunschweig, Munich, and Berlin, its mean coverage over complete chains stays within 0.245 percentage points of full-set greedy under the same policy, with 13.6--28.9 times lower mean rollout time. CLIPPER-A instead distributes one shared candidate budget across the groups. Under its coverage-prioritized policy, it uses 9--15% of full-set greedy's rollout time under the same policy, with mean gaps of 1.82 percentage points in Braunschweig, 0.12 in Munich, and 0.27 in Berlin. Together, CLIPPER enables rapid, replayable comparison of recorded city-scale planning states while enforcing every encoded model constraint.
CommentsAccepted at ACM SIGSPATIAL 2026. 6 pages, 2 figures, 2 tables
