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Development of an Optimization Methodology for Adaptive Traffic Signal Control at Diamond Interchanges

机译:钻石交汇处自适应交通信号控制优化方法的开发

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This research develops a methodology and a corresponding implementation algorithm to provide optimal signal control of diamond interchanges in response to real-time traffic fluctuations. The problem is formulated as to find a phase sequencing decision with a phase duration that makes a prespecified performance measure minimized over a finite horizon that rolls forward. The problem is solved by a forward dynamic programming (DP) method. The optimal signal switches over each 2.5 s interval are found for each horizon of 10 s. The optimization process is based on the advanced vehicle information obtained from loop detectors set back a certain distance from the stop line. Vehicle trajectories from detections till future arrivals and departures is modeled at the microscopic level to estimate the traffic flows at the stop-line for each horizon. The DP algorithm is coded in C++ language and dynamically linked to AIMSUN, a stochastic microsimulation package, for evaluation. The simulation results have exhibited that the DP algorithm is superior to PASSER Ⅲ and TRANSYT-7F in handling demand fluctuations for medium to high flow scenarios when the field demand is increased from the one used in off-line optimization. The performance of the three algorithms is almost identical if the simulation demand is similar to off-line demand situation and does not vary much.
机译:这项研究开发了一种方法和相应的实现算法,以响应实时交通波动提供最佳的钻石换乘信号控制。制定问题的方式是找到具有阶段持续时间的阶段排序决策,该阶段持续时间可以使预先指定的性能指标在向前滚动的有限范围内最小化。通过前向动态编程(DP)方法解决了该问题。对于每个10 s的水平,找到每个2.5 s间隔的最佳信号切换。优化过程基于从环路检测器获得的高级车辆信息,该环路检测器将距停止线一定距离。从检测到未来到达和离开的车辆轨迹在微观水平上建模,以估计每个地平线在停车线处的交通流量。 DP算法用C ++语言编码,并动态链接到随机微仿真程序包AIMSUN进行评估。仿真结果表明,当现场需求从离线优化中增加时,DP算法在处理中到高流量情况下的需求波动方面优于PASSERⅢ和TRANSYT-7F。如果模拟需求类似于离线需求情况并且变化不大,则这三种算法的性能几乎相同。

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