Bi-level programming model of timing optimization for multiple bus priority intersection
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摘要: 公交优先感应信号控制会对非优先相位车辆产生不利影响, 为了均衡非优先相位的损失, 降低交叉口及下游公交站台的乘客延误, 建立了多路公交优先交叉口配时优化的双层规划模型。上层模型描述了基于交叉口延误以及下游公交站台乘客排队延误的优先策略时长优化, 下层模型在计算交叉口停驶-加速延误的基础上描述了各相位绿时损失的均衡过程, 以优先策略时长为决策变量, 将优先策略的影响引入到下层模型。利用Gauss-Seidel迭代法设计了求解算法, 并进行了实例分析。分析结果表明: 配时优化后, 周期内交叉口和下游站台乘客的总延误减少了23 576.12s, 同时交叉口车辆停驶-加速延误减少了62.87s, 双层规划模型在公交优先的前提下保障了交叉口的整体效益。Abstract: Induction signal control based on bus priority had negative effects on vehicles in nonpriority phases. In order to equilibrate the loss of non-priority phases, as well as to reduce the passenger delay at the intersection and the downstream stations, a bi-level programming model of signal timing optimization for multiple bus priority intersection was proposed. In the upper model, priority strategies were optimized based on the intersection delay and the passenger queuing delay at downstream stations. In the lower model, the equilibrium process of green loss was described based on the calculation of acceleration-deceleration delay at the intersection. With priority strategies as decision-making variables, the influence of priority strategies was introduced to the lower model. The solution algorithm was designed by using the Gauss-Seidel iterative method. An application example was analyzed. Analysis result indicates that after signal timing optimization, total passenger delays at the intersection and downstream stations in the period reduces by 23 576.12 s. Besides, the vehicle acceleration-deceleration delay at the intersection reduces by 62.87s. Bi-level programming model ensures the overall efficiency at the intersection under consideration of bus priority.
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图 7 同一时刻GE-PI策略的绿时损失均衡
Figure 7. Green loss equilibrium of GE-PI strategy at same time
图 8 同一时刻PI-RT策略的绿时损失均衡
Figure 8. Green loss equilibrium of PI-RT strategy at same time
图 9 同一时刻PI-PI策略的绿时损失均衡
Figure 9. Green loss equilibrium of PI-PI stratgey at same time
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