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Augmenting Traffic Signal Control Systems for Urban Road Networks With Connected Vehicles

机译：用连通车辆增强城市公路网的交通信号控制系统

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The increase in traffic volumes in urban areas makes network delay and capacity optimisation challenging. However, the introduction of connected vehicles in intelligent transport systems presents unique opportunities for improving traffic flow and reducing delays in urban areas. This paper proposes a novel traffic signal control algorithm called Multi-mode Adaptive Traffic Signals (MATS) which combines position information from connected vehicles with data obtained from existing inductive loops and signal timing plans in the network to perform decentralised traffic signal control at urban intersections. The MATS algorithm is capable of adapting to scenarios with low numbers of connected vehicles, an area where existing traffic signal control strategies for connected environments are limited. Additionally, a framework for testing connected traffic signal controllers based on a large urban road network in the city of Birmingham (UK) is presented. The MATS algorithm is compared with MOVA on a single intersection, and a calibrated TRANSYT plan on the proposed testing framework. The results show that the MATS algorithm offers reductions in mean delay up to 28% over MOVA, and reductions in mean delay and mean numbers of stops of up to 96% and 33% respectively over TRANSYT, for networks with 0-100% connected vehicle presence. The MATS algorithm is also shown to be robust under non-ideal communication channel conditions, and when heavy traffic demand prevails on the road network.
机译：城市地区交通量的增加使网络延迟和能力优化具有挑战性。然而，在智能运输系统中引入连接的车辆为改善交通流量和降低城市地区延误提供了独特的机会。本文提出了一种新的交通信号控制算法，称为多模式自适应交通信号（垫），其将来自连接的车辆的位置信息与从现有的电感环路获得的数据组合，并且网络中的信号定时计划在城市交叉口执行分散的交通信号控制。垫算法能够适应具有较低连接车辆的场景，该区域是连接环境的现有交通信号控制策略的区域。此外，还提出了一种基于伯明翰（英国）市基于大型城市公路网络的连接交通信号控制器的框架。将垫算法与单个交叉点上的MOVA进行比较，以及在所提出的测试框架上进行校准的Transyt计划。结果表明，垫算法的平均延迟减少高达28％的MOVA，并且在Tyroryt中分别在Tyroryt中减少平均延迟和平均止损数，可分别为0-100％连接车辆的网络。在场。在非理想的通信信道条件下，垫算法也被稳健，并且在道路网络上占有繁忙的交通需求。

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