解决城市空中交通中垂直起降场调度的动态需求与模糊指令问题
Intent-Driven UAM Rescheduling
- 用三值逻辑解析人类模糊意图，结合决策树增强可解释性
- 融合答案集编程与混合整数规划，实现动态调度优化
- 适合关注智能交通系统可解释调度的科研与工程人员
由于资源受限，城市空中交通（UAM）中的垂直起降场高效调度受到广泛关注。针对调度问题，本文采用混合整数线性规划（MILP），其通常被建模为资源受限项目调度问题（RCPSP）。本研究提出一种新方法，以应对动态运行需求和来自人类的模糊重调度请求。特别地，采用三值逻辑来解释模糊用户意图，并结合决策树，构建了一个集成答案集编程（ASP）与MILP的新系统。该框架在优化调度的同时，透明支持人类输入，提供可解释、自适应的UAM调度结构。
原文摘要 · Abstract (English)
Due to the restricted resources, efficient scheduling in vertiports has received much more attention in the field of Urban Air Mobility (UAM). For the scheduling problem, we utilize a Mixed Integer Linear Programming (MILP), which is often formulated in a resource-restricted project scheduling problem (RCPSP). In this paper, we show our approach to handle both dynamic operation requirements and vague rescheduling requests from humans. Particularly, we utilize a three-valued logic for interpreting ambiguous user intents and a decision tree, proposing a newly integrated system that combines Answer Set Programming (ASP) and MILP. This integrated framework optimizes schedules and supports human inputs transparently. With this system, we provide a robust structure for explainable, adaptive UAM scheduling.
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