基于Agent的集体和自主航天飞机自组织框架
Agent-based Framework for Self-Organization of Collective and Autonomous Shuttle Fleets
摘要：
人的流动性是未来城市交通规划和决策的中心。为了加快向零排放的过渡，并最大限度地提高空气质量效益，智慧城市正在优先考虑步行、骑自行车、共享移动服务和公共交通，而不是使用私家车。在自动驾驶汽车和电动汽车方面取得了广泛的进展。自动驾驶汽车（AV）越来越能够在没有人类完全控制的情况下移动，自动驾驶的某些方面，如转向或制动。出于这些原因，城市正在投资基础设施和技术，以支持包括共享电动自动驾驶汽车（AV）在内的互联多模式交通网络。传统公共交通与新型出行服务之间的关系备受关注，需要重新思考。本文提出了一个基于代理的仿真框架，允许创建和模拟的移动场景，调查新的移动模式对城市日常生活的影响。它让交通规划者探索使用分散控制方法的AV的合作集成。一个原型已经实施，并验证了特伦托市的数据。
英文摘要：
The mobility of people is at the center of transportation planning and decision-making of the cities of the future. In order to accelerate the transition to zero-emissions and to maximize air quality benefits, smart cities are prioritizing walking, cycling, shared mobility services and public transport over the use of private cars. Extensive progress has been made in autonomous and electric cars. Autonomous Vehicles (AV) are increasingly capable of moving without full control of humans, automating some aspects of driving, such as steering or braking. For these reasons, cities are investing in the infrastructure and technology needed to support connected, multi-modal transit networks that include shared electric Autonomous Vehicles (AV). The relationship between traditional public transport and new mobility services is in the spotlight and need to be rethought. This paper proposes an agent-based simulation framework that allows for the creation and simulation of mobility scenarios to investigate the impact of new mobility modes on a city daily life. It lets traffic planners explore the cooperative integration of AV using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
