Abstract: Reversible variable lane is considered an effective traffic organization method to alleviate intersection congestion caused by the imbalance between the supply and demand of left-turning vehicle flow. Efficiency index calculation models applicable to different saturation levels were introduced to establish a dual-objective optimization model for reversible variable lane design maximizing traffic capacity and minimizing delay. A hybrid algorithm combining with multi-objective evolutionary algorithm (MOEA) and non-dominated sorting genetic algorithm II (NSGA-Ⅱ) was employed to solve for the timing and spatial geometric parameters required for calculating the setting of reversible variable lanes. The effectiveness of the proposed optimization model under three different traffic flow loads, namely low, medium and high, was validated by VISSIM simulation. Meanwhile, based on the time non-stationarity of traffic flow load during peak hours, the optimal recommended scheme for reversible variable lanes was determined under three traffic flow ratio scenarios: continuous, concentrated, and balanced. The results show that under the combined effect of the setting of reverse variable lanes and the signal timing parameters obtained from the optimization model, the average vehicle delay at intersections under three different traffic flow loads is respectively decreased by 13.14%, 16.38%, and 23.34%, the number of stops is respectively decreased by 16.86%, 12.24% and 33.19%, and the queue length is respectively decreased by 18.62%, 24.43%, and 32.41%. Under fluctuating traffic flow conditions, the impact of time non-stationarity on the selection of the balanced flow scheme is relatively small. However, continuous and concentrated traffic flows characterized by prominent oversaturated traffic flow require variable lanes of sufficient length to assist vehicle traffic. In actual timing, it is necessary to comprehensively consider the proportion of arriving traffic volume. Simply considering the cycle and pre-signal design scheme under the maximum flow background will exacerbate the overall delay at intersections.

Key words: traffic engineering; traffic signal control; reversing variable lane; timing optimization; multi-objective optimization; temporal non-stationarity

摘要： 逆向可变车道被认为是缓解因左转车流供需不均衡而引发的交叉口阻塞的一种有效交通组织方法，引入适用不同饱和度的效率指标计算模型，建立通行能力最大化、延误最小化的逆向可变车道设计双目标优化模型，采用多目标进化算法（MOEA）与非支配排序遗传算法Ⅱ（NSGA-Ⅱ）的混合算法，求解计算逆向可变车道设置所需的配时与空间几何参数。利用VISSIM仿真验证了低、中、高3种不同流量负荷下的优化模型有效性，同时基于高峰小时交通流量负荷的时间非平稳性，在持续型、集中型和均衡型3种流量配比情景下，确定逆向可变车道的最优推荐方案。结果表明：逆向可变车道设置与优化模型求解的信号配时参数共同作用下，3种交通流量负荷下交叉口的车均延误分别降低13.14%、16.38%、23.34%，停车次数下降16.86%、12.24%、33.19%，排队长度降低18.62%、24.43%、32.41%；波动流量下，时间非平稳性对均衡流量的方案选择影响较小，过饱和流量突出的持续型和集中型情境需要足够长度的可变车道辅助车辆通行，且在实际的配时中，需综合考虑到达交通量的配比，仅考虑最大流量背景下的周期与预信号设计方案会加剧交叉口整体延误。

关键词: 交通工程；交通信号控制；逆向可变车道；配时优化；多目标优化；时间非平稳性