Self-organizing and self-regulating coordination of a large swarm of self-navigating autonomous vehicles as occuring in traffic

交通中出现的一大群自导航自动驾驶车辆的自组织和自调节协调

• 批准号: 5453754
• 负责人: Professor Dr. Sándor Fekete
• 金额: --
• 依托单位: Institut für Betriebssysteme und Rechnerverbund
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2005
• 资助国家: 德国
• 起止时间: 2004-12-31 至 2012-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5453754?language=en
• 关键词: Self; organizing; self; regulating; coordination

The objective of our project AUTONOMOS is the development a distributed and self-regulated aproach for the organization of a large system many self-driven, mobile objects. Based on methods for ad-hoc networks using short-distance comunication betwen vehicles, and ideas from distributed algorithms, local data clouds are formed in reaction to specific trafic structures (e.g., jams). These Hovering Data Clouds HDCs) are used for forming Organic Information Complexes (OICs) that are functional entities within the trafic flow, hosted by—but independent of—individual moving vehicles (e.g., for detecting, indicating and monitoring the structure of a trafic jam that continues to exist in place, even as the involved vehicles axe replaced.) Using HDC-based OICs, we develop Adaptable Distributed Strategies (ADSs) for dealing with complex and changing trafic situations. A final goal is thextension to achieve Global Objectives for vehicles and trafic flow. Our project is based on a wel-established interdisciplinary coperation and combines practical know-how from the field of mobile ad-hoc networks with theoretical expertise'from a wide range of algorithmic topics. While the firsthre years our six-year project dealt with largely local phenomena like trafic flow and their improvement, the goal for second half is thextension of our work to even more complex concepts, methods, and structures, with an emphasis on overal scenarios

我们 AUTONOMOS 项目的目标是开发一种分布式和自我调节的方法，用于组织大型系统的许多自驱动、移动对象。基于使用车辆之间短距离通信的自组织网络方法以及分布式算法的思想，根据特定的交通结构（例如拥堵）形成本地数据云。这些悬停数据云（HDC）用于形成有机信息复合体（OIC），有机信息复合体是交通流中的功能实体，由单个移动车辆托管但独立于单个移动车辆（例如，用于检测、指示和监控持续存在的交通拥堵的结构，即使涉及的车辆被替换）。使用基于 HDC 的 OIC，我们开发了自适应分布式策略（ADS）： 应对复杂多变的交通状况。最终目标是扩展以实现车辆和交通流量的全球目标。我们的项目基于完善的跨学科合作，并将移动自组织网络领域的实用知识与广泛算法主题的理论专业知识相结合。虽然我们的六年项目的前三年主要处理交通流量及其改善等局部现象，但下半年的目标是将我们的工作扩展到更复杂的概念、方法和结构，重点是总体场景