利用反向流和冲突消除进行人车混行疏散路网优化

城市突发事件时人员会选择不同的交通方式（步行、驾车等）进行疏散，在交叉口处极易出现人车混行。提出了一种利用反向流和冲突消除策略的人车混行疏散路网优化方法，对主要疏散路径进行人、车流的反向以扩大通行能力，并在交叉口处禁止人、车的部分转向来进行人车分流以消减人车冲突。建立了以平均疏散时间和平均疏散路径长度最小为目标的优化模型，并利用遗传算法求解最优的人车分流方案。以武汉市2 km范围内的路网为例进行实验，并针对不同的人车混合比例进行模型敏感性分析。结果表明，所提方法能通过人车混行网络设计提高疏散效率，在行人比例较高的情况下，平均疏散时间及疏散路径长度的改善较明显。

Evacuation Network Optimization Based on Contraflow and Conflict Elimination for Pedestrian-Vehicle Mixed Flows

People under emergencies will choose different traffic modes (walking, driving, etc.) for evacuation. In this circumstance, the conflicts of the mixed flows (pedestrians and vehicles) at various locations in the network can be critical to the operational efficiency of the evacuation activities. This paper proposes an evacuation network optimization approach based on conflict elimination and contraflow strategy by separating pedestrian and vehicle flows with physical barriers at road intersections and reverse pedestrians and vehicles on main evacuation routes, respectively. A multi-objective optimization model is formulated to determine the appropriate locations of barriers or blocks in the evacuation network. A genetic based algorithm is developed to solve the optimization problem. The proposed model is tested for an evacuation zone with the area of 2 km2 in Wuhan city. Besides, the sensitivity analysis is implemented for different mixing ratios of pedestrians and vehicles. The results show that the proposed approach can effectively separate pedestrian and vehicle flows at intersections to improve the evacuation efficiency, and the improvements are greater when pedestrians take a higher percentage in the evacuation system.