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解锁相互利益 - - 一项关于在城市环境中协作自动驾驶的实验研究

Sumbal Malik^1,2, Manzoor Ahmed Khan^1,2, Hesham El-Sayed^1,2

¹College of Information Technology, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates.

Sensors (Basel, Switzerland)

|January 11, 2024

概括

车队驾驶或协作自动驾驶可以改善交通流量并减少排放. 这项研究模拟了保险折扣等激励措施,以鼓励个人参与汽车,平衡社会和个人利益.

科学领域:

运输工程运输工程
自主系统自主系统
游戏理论游戏理论

背景情况:

车队驾驶提供了社会效益,如减少拥堵和排放.
车队中的个人车辆参与至关重要,但经常被忽视.
现有的研究优先考虑集体利益而不是个人激励.

研究的目的:

模拟车队驾驶的社会效益 (交通流量,排放).
设计和建模车队参与的个人级激励措施.
弥合社会目标和个体车主动机之间的差距.

主要方法:

使用基本图表建模混合流量流.
整合互联自动驾驶汽车 (CAV) 透率,联盟强度和规模.
应用联盟游戏理论来模拟协作车队驾驶.
开发一种新的公用事业功能,并提供激励措施 (保险,罚款,收费).

主要成果:

基于CAV透率,联盟强度和大小分析混合流量流动.
确定需要平衡CAV透率,联盟因素和速度以获得最佳效益.
证明了拟议的激励措施在鼓励车队组成方面的有效性.

结论:

车队驾驶需要将道路当局的可持续性目标与车辆所有者的个人利益相协调.
在CAV整合和激励设计方面,一个平衡的方法是关键.
这项研究促进了车队驾驶的互利未来.

关键词:

联盟游戏联盟游戏协同驾驶的合作驾驶.一个车队的车队.激励方式激励方式污染物排放排放的污染物.交通流量交通流量流量城市环境城市环境

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