Dynamic Signal Coordination for Networks with Oversaturated Intersections
Dynamic Signal Coordination for Networks with Oversaturated Intersections
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DOI：
10.3141/1811-15
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发表时间：
2002
影响因子：
1.7
通讯作者：
Montty Girianna;R. Benekohal
中科院分区：
文献类型：
--
作者：
Montty Girianna;R. Benekohal
提出了一种针对过饱和交叉口网络的信号协调设计算法。应用于过饱和单条干线的信号协调的基本概念被扩展到干线网格网络，这涉及更大的分析和计算复杂性。在该算法中，信号协调被表述为动态优化问题。该问题的开发是为了协调沿着穿过多个平行协调干线的干线的过饱和信号。沿交叉干道的信号也过饱和。在过饱和期间，该算法通过将本地队列空间分布在多个信号交叉口并临时将其分布在信号周期内来管理本地队列。根据交通需求的变化和关键信号的位置，该算法可以智能地生成各条主干道上的最佳信号配时（绿灯时间和偏移量）。如果关键信号位于出口点，该算法会设置最佳信号时序，以防止它们过载。如果关键信号位于入口点，该算法可确保在释放的排到达下游信号系统之前减少或清除队列。此外，该算法最终找到一组从上游信号传播的公共周期，从而促进流量进展。采用微遗传算法解决信号优化问题。该算法在具有 20 个信号的单向动脉系统上进行了测试。结果表明，该算法成功地管理了协调干道上的队列，使信号机分担了交通负担，并为指定方向上的交通发展创造了机会。
An algorithm to design signal coordination for networks with oversaturated intersections is presented. The basic concept of signal coordination applied to oversaturated single arterials is extended for a grid network of arterials, which involves greater analytical and computing complexity. In this algorithm, signal coordination is formulated as a dynamic optimization problem. The problem is developed to coordinate oversaturated signals along an arterial that crosses multiple, parallel coordinated arterials. Signals along crossing arterials are also oversaturated. During an oversaturated period, the algorithm manages local queues by spatially distributing them over a number of signalized intersections and by temporarily spreading them over signal cycles. Depending on the traffic demand’s variation and the position of critical signals, the algorithm intelligently generates optimal signal timing (green times and offsets) along individual arterials. If critical signals are located at the exit points, the algorithm sets the optimal signal timing that protects them from becoming excessively loaded. If critical signals are located at the entry points, the algorithm ensures that queues are reduced or cleared before released platoons arrive at a downstream signal system. In addition, the algorithm eventually finds a set of common cycles propagated from upstream signals, thus promoting traffic progression. The micro-genetic algorithm was used to solve the signal optimization problem. The algorithm was tested on a one-way arterial system with 20 signals. The results indicate that the algorithm successfully managed queues along coordinated arterials, made the signals share the burden of traffic, and created the opportunity for traffic progression in specified directions.