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Journal of Zhejiang University SCIENCE A
ISSN 1673-565X(Print), 1862-1775(Online), Monthly
2025 Vol.26 No.8 P.801-810
A real-time adaptive signal control method for multi-intersections in mixed connected vehicle environments
Abstract: With the advancement of connected vehicle (CV) technology, an increasing number of CVs will appear on urban roads. Data collected by CVs can be used to optimize signal parameters at intersections, thus improving traffic efficiency. In this study, we design a real-time adaptive signal control method for an arterial road with multiple intersections with low penetration rates. By utilizing vehicle arrival information collected by CVs, our method rapidly determines optimal signal phasing and timing (SPaT). The proposed adaptive signal control method was tested with the Simulation of Urban Mobility (SUMO) software, and was found to reduce total travel delay in the network better than a fixed coordination control method. The performance of the proposed method in reducing travel delay is expected to improve as CV detection range increases.
Key words: Adaptive traffic signal control; Connected vehicle (CV); Travel delay; Arterial road control
机构：宁波大学，海运学院，中国宁波，315211
目的：传统基于路侧交通传感器采集数据的信号配时参数优化方法不能及时地获取实时的交通流运行状况，而网联车辆收集的实时数据可用于优化交叉口的信号控制参数，从而提高交通运行效率。本研究设计了一种适用于低渗透率多交叉口主干道的实时自适应信号控制方法。通过利用部分网联车辆收集的车辆到达信息，以快速确定最优信号相位和时序（SPaT），优化干线上各交叉口信号配时参数以提升交通运行效率。
创新点：1.设计了适用于低网联车渗透水平条件下的干线自适应信号控制方法，有效利用部分网联车辆采集的实时交通流数据优化信号配时参数，减少干线上车辆行驶延误；2.所提出的自适应信号控制方法考虑了网联车辆的探测距离，并在SUMO仿真软件中进行了模拟实验验证其有效性。
方法：1.通过所设计的干线自适应信号控制策略的整体框架，建立完整的适用于部分网联车辆环境下的信号参数优化控制流程（图2）；2.通过建立的自适应信号控制优化模型，利用网联车辆采集到的实时交通流信息优化每个信号周期的信号配时方案（公式(1)~(5)）；3.通过微观交通仿真软件SUMO对所提出的干线自适应信号控制策略进行验证，并将所提信号控制策略的性能与传统方法进行比较（表2~4，图4）。
结论：1.利用网联车辆收集的实时交通流数据动态优化主干道上各交叉口的SPaT可以有效的减少干线上车辆的行驶延误；2.在智能网联环境下，只利用部分网联车辆采集的数据即可满足交叉口信号参数优化所需的数据量；3.网联车辆的探测距离比网联车辆的渗透率对所提策略控制性能的影响更大。
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DOI:
10.1631/jzus.A2400488
CLC number:
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On-line Access:
2025-08-27
Received:
2024-10-15
Revision Accepted:
2024-12-05
Crosschecked:
2025-08-28