为处理交通流不确定性,提高交通信号控制方案的可靠性,结合非线性区间规划理论,提出交叉口信号配时参数区间优化模型。首先,在高峰时段以5min为采集标段对交叉口进行数据统计,并以此构造交通流量区间来区间化不确定参数;其次,以交通流量区间为控制系统输入参数,结合区间数理论,构建以机动车平均延误区间最小为目标的交叉口信号配时参数区间优化模型;然后,利用区间序关系和可能度模型进行模型转换,运用双层嵌套遗传算法进行求解;最后,选取北京市两个两相位交叉口进行模型验证与仿真比较。结果表明:信号配时区间优化模型是可行、有效的,且更适合于交通需求波动较大的交叉口,相较于实测数据,该区间优化模型车均延误减少了17.16%,通行能力提高了1.19%,且相较于传统控制方案,该模型提高了信号控制方案运行的稳定性。

In order to deal with the uncertainty of traffic flow and improve the reliability of traffic signal control scheme, combined with the theory of nonlinear interval programming, an interval optimization model of intersection signal timing parameters was proposed. Firstly, traffic flow interval were constructed to interval uncertain parameters based on taking five minutes during peak period as the acquisition section for data statistics of intersections. Secondly, combined with the interval number theory, a signal timing parameters interval optimization model that minimized vehicle average delay interval was established by taking the traffic flow interval as the input parameters. Thirdly, the proposed model was transformed into the deterministic mathematical model by using the interval order relation and possibility degree model, and solved by a double nested genetic algorithm. Finally, two intersections with two-phase in Beijing were chosen for model verification and simulation comparison. The results show that the interval optimization method is feasible and effective, and more suitable for the intersection with large fluctuation of traffic demand. Using this interval optimization method, the vehicle average delay is reduced by 17.16% and capacity is increased by 1.19% compared with the measured data. Furthermore, compared with the traditional method, the stability of signal control scheme can be improved by this optimization method.