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Hierarchical control of heterogeneous large-scale urban road networks via path assignment and regional route guidance

机译:通过路径分配和区域路线引导对异构大型城市道路网络进行分层控制

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摘要

High level of detail renders microscopic traffic models impractical for control purposes and local control schemes cannot coordinate actions over large scale heterogeneously congested urban networks. Developing efficient models and control methods for large-scale urban road networks is, therefore, an important research challenge. Alleviating congestion via manipulation of traffic flows or assignment of vehicles to specific paths has a great potential in achieving efficient network usage. Motivated by this fact, this paper proposes a hierarchical traffic management system. The upper-level route guidance scheme builds a model predictive control (MPC) scheme and optimizes network performance based on actuation via regional split ratios, whereas the lower-level path assignment mechanism develops an integer linear programming (ILP) formulation and recommends subregional paths for vehicles to follow, satisfying the regional split ratios in order to achieve said performance. Simulation results from a 49-subregion or 7-region network shows a great potential of the proposed scheme in achieving coordination and efficient use of network capacity, leading to increased mobility.
机译:高级别的详细信息使微观交通模型无法实现控制目的,并且本地控制方案无法协调大规模异类拥堵城市网络上的行动。因此,为大型城市道路网络开发有效的模型和控制方法是一项重要的研究挑战。通过操纵交通流或将车辆分配到特定路径来缓解拥塞,在实现有效的网络使用方面具有巨大的潜力。基于这一事实,本文提出了一种分层交通管理系统。上级路线引导方案建立了模型预测控制(MPC)方案,并基于通过区域分配比率的促动来优化网络性能,而下级路径分配机制则开发了整数线性规划(ILP)公式并建议用于以下目的的子区域路径满足区域划分比率的车辆,以实现上述性能。来自49个子区域或7个区域的网络的仿真结果表明,该方案在实现网络容量的协调和有效利用方面具有巨大潜力,从而可以提高移动性。

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