用CARLA模拟电动叉车在仓库中的运行与能耗，支持交通分析和充电站规划。
A CARLA-based Simulation of Electrically Driven Forklifts
- 基于CARLA构建3D仓库场景，模拟多辆叉车的实时移动与路径规划。
- 集成物理电池模型，实时计算每辆叉车的电量状态（SOC）变化。
- 适用于物流优化、交通拥堵检测与充电站布局设计，适合智能仓储研究者。
本文提出在智能物流场景中使用开源仿真工具CARLA对电动叉车车队进行仿真。首先，利用CARLA生成并可视化一个包含随机移动叉车的逼真三维室外仓库环境；随后，模拟了包括拣选-放置在内的物流运输任务，并实现最短路径规划。此外，演示了回放真实叉车车队采集的定位数据的能力，可在原场景中重现叉车运动轨迹。最后，通过集成物理电池模型，模拟叉车在负载与作业活动下的能量消耗，输出各车辆的电量状态（SOC）。为展示平台的广泛应用潜力，文中描述了两个典型用例：一是识别交通密度异常高的区域，二是优化叉车充电站的部署位置。两项应用均基于一个示例仓库模型完成。
原文摘要 · Abstract (English)
This paper presents the simulation of the operation of an electric forklift fleet within an intralogistics scenario. For this purpose, the open source simulation tool CARLA is used; according to our knowledge this is a novel approach in the context of logistics simulation. First, CARLA is used to generate and visualize a realistic 3D outdoor warehouse scenario, incorporating a number of randomly moving forklifts. In a next step, intralogistics transport tasks, such as pick-and-place, are simulated for the forklift fleet, including shortest-path finding. Furthermore, the capability to play back localization data, previously recorded from a ''real'' forklift fleet, is demonstrated.This play back is done in the original recreated environment, thereby enabling the visualization of the forklifts movements. Finally, the energy consumption of the forklift trucks is simulated by integrating a physical battery model that generates the state of charge (SOC) of each truck as a function of load and activity. To demonstrate the wide range of possible applications for the CARLA simulation platform, we describe two use cases. The first deals with the problem of detecting regions with critically high traffic densities, the second with optimal placement of charging stations for the forklift trucks. Both use cases are calculated for an exemplary warehouse model.
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