论文推荐 | 城市非机动车交通仿真：基于自行车共享大数据和社会力模型的智能体建模方法-规划问道

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本期为大家推荐的内容为论文《Simulation of urban non-motorized traffic: A agent-based modeling approach based on big data of bike sharing and social force model》（城市非机动车交通仿真：基于自行车共享大数据和社会力模型的智能体建模方法），发表在Transactions in Urban Data, Science, and Technology期刊，欢迎大家学习与交流。

鼓励使用自行车这种城市非机动交通方式已被广泛认可为一种环境友好的方式，它可以缓解城市交通拥堵并解决“最后一公里”问题。然而，由于自行车道权利不明确和非机动车道不连续，城市规划者对城市骑行的效率和安全性普遍表示担忧。本研究利用深圳高科技园区美团自行车（前身为摩拜单车）的动态位置数据，分析共享自行车使用的时空变化，旨在识别自行车交通走廊。结合基于智能体的建模技术和社会力模型，本研究提出了一种新的模拟城市非机动交通的方法，因此为建设自行车走廊的自行车道提供了宝贵的洞见。结果显示：（1）工作日共享自行车的使用量是周末的2.5倍，骑行走廊通常是靠近地铁站的主要和次要道路；（2）增加自行车道可以将非机动车流量的交通密度整体降低6%，并分别节省自行车骑行者和行人的出行时间6.4%和3.7%。

论文推荐 | 城市非机动车交通仿真：基于自行车共享大数据和社会力模型的智能体建模方法

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题目：Simulation of urban non-motorized traffic: A agent-based modeling approach based on big data of bike sharing and social force model

（城市非机动车交通仿真：基于自行车共享大数据和社会力模型的智能体建模方法）

作者：

Wenke Huang, Yuanyuan Guo*, Cong Guo, Fengliang Tang, Yingping Zhao, Zihui Xia, and Runhao Zhang

发表刊物：

Transactions in Urban Data, Science, and Technology

DOI:

https://doi.org/10.1177/27541231231180989

引用格式：

Huang, W., Guo, Y., Guo, C., Tang, F., Zhao, Y., Xia, Z., & Zhang, R. (2023). Simulation of urban non-motorized traffic: A agent-based modeling approach based on big data of bike sharing and social force model. Transactions in Urban Data, Science, and Technology, 27541231231180989.

摘要ABSTRACT

Encouraging cycling, one of the urban non-motorized transport modes, has been well recognized as an environment-friendly way that alleviates urban traffic congestions and solves the first/last mile issue. However, concerns about the efficiency and safety of urban cycling have been widely made by urban planners due to the unclear right-of-way and discontinuous non-motorized corridor for cycling. This study uses the dynamic location data of the Meituan Bike (formerly Mobike) in the Hi-tech Park area of Shenzhen to analyze the spatial-temporal variations of bikeshare use, aiming at identifying the traffic corridors of cycling. Combined with agent-based modeling technique and social force model, this research proposes a new approach of simulating the urban non-motorized traffic, and hence provides valuable insights for building bicycle lanes for cycling corridors. The results show that (1) the usage of bike sharing during weekdays is 2.5 times that on weekdays, and the cycling corridors are usually the main and secondary roads that are in the vicinity of the metro stations; (2) adding bicycle lanes can reduce the traffic density of the non-motorized volume by 6% in an overall, and save the travel time of cyclists and pedestrians by 6.4% and 3.7%, respectively.