基于时空等待特征系数的大型活动出行规划研究

Efficient and reasonable integrated traffic path planning is one of the prerequisites for successful large-scale events. In this paper, we introduce passenger travel preferences for a routing problem of mass groups participating in large events and convert it into a space-time waiting optimization problem. A space-time-transport mode network is constructed based on the characteristics of multi-modal public transportation. An integer linear programming model is developed to minimize the total cost of passenger travel time. To improve the efficiency of solving real-scale datasets, an algorithm based on Lagrangian relaxation and sub-gradient optimization is proposed. A search space reduction method based on inverse inference is introduced to improve the algorithm. The proposed model and algorithm are validated with a hypothetical case of audiences going to watch the Olympic game. The numerical results show that the introduction of time-space waiting improves the rationality of the travel path planning scheme for large-scale events, as well as improving the travel experience of passengers. It is also proved that the model alleviates traffic congestion effectively when large-scale events are held.