Scholarlink

To improve the efficiency of urban transportation systems and reduce congestion, this article focuses on the problem of dynamic traffic flow assignment with uncertain multimodal transportation demand. The objective is to minimize travel costs for commuters. We constructed a multimodal dynamic traffic flow allocation model with road capacity and solved it by combining variational inequalities with the MSA algorithm. The example analysis shows that the traffic volume allocation of different travel modes conforms to the Logit probability selection function, and the increase in the road network information perception coefficient makes travel mode selection more deterministic. This provides a new perspective for urban transportation planning and management.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Research on Elastic Demand Assignment of Multi-modal Urban Traffic Flow

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Yangyang Chen,
  • Juhua Yang,
  • Jianjun Wang,
  • Qing Song,
  • Shilin Qu

摘要

To improve the efficiency of urban transportation systems and reduce congestion, this article focuses on the problem of dynamic traffic flow assignment with uncertain multimodal transportation demand. The objective is to minimize travel costs for commuters. We constructed a multimodal dynamic traffic flow allocation model with road capacity and solved it by combining variational inequalities with the MSA algorithm. The example analysis shows that the traffic volume allocation of different travel modes conforms to the Logit probability selection function, and the increase in the road network information perception coefficient makes travel mode selection more deterministic. This provides a new perspective for urban transportation planning and management.