Hu Yingyue, Long Huizhen, Chen Min
School of Government, Central University of Finance and Economics, Beijing, 10081, China.
Strategic Planning Office, Wuhan Business University, Wuhan, China.
Sci Rep. 2024 May 20;14(1):11456. doi: 10.1038/s41598-024-62134-8.
With the acceleration of urbanization in China, the urban population continues to grow, leading to frequent occurrences of crowded public spaces, which in turn trigger traffic congestion and even safety accidents. In order to more effectively control pedestrian flow, enhance the efficiency and safety of public spaces, this experiment conducts in-depth research and improvement on the traditional Dynamic Window Approach (DWA), and applies it to the fine control of pedestrian flow. Specifically, this study comprehensively reviews and analyzes the characteristics of pedestrian traffic flow and the working principles of traditional DWA. Based on this, the shortcomings of traditional DWA in dealing with complex pedestrian flow scenarios are identified, and targeted improvement solutions are proposed. The core of this improvement scheme lies in the introduction of a new evaluation function, enabling DWA to more accurately balance various factors in the decision-making process, including pedestrian movement speed, direction, and spatial distribution. Subsequently, the improved DWA is validated through simulation experiments. The experimental scenario is set in an area of 18 m*18 m, and compared with traditional DWA, the improved DWA shows significant advantages in trajectory length and travel time. Specifically, the trajectory length of the traditional DWA robot is 19.4 m, with a required time of 34.8 s, while the trajectory length of the improved DWA robot is shortened to 18.7 m, and the time is reduced to 18.6 s. This result fully demonstrates the effectiveness of the improved DWA in optimizing pedestrian flow control. The improved DWA proposed in this study not only has strong scientific validity but also demonstrates high efficiency in practical applications. This study has important reference value for improving the safety of urban public spaces and improving pedestrian traffic flow conditions, and provides new ideas for the further development of pedestrian flow control technology in the future.
随着中国城市化进程的加速，城市人口持续增长，导致公共场所拥挤现象频繁发生，进而引发交通拥堵甚至安全事故。为了更有效地控制人流，提高公共场所的效率和安全性，本实验对传统的动态窗口方法（DWA）进行了深入研究和改进，并将其应用于人流的精细控制。具体而言，本研究全面回顾和分析了行人交通流的特征以及传统DWA的工作原理。在此基础上，找出了传统DWA在处理复杂人流场景时的不足，并提出了针对性的改进方案。该改进方案的核心在于引入了一种新的评估函数，使DWA能够在决策过程中更准确地平衡各种因素，包括行人移动速度、方向和空间分布。随后，通过仿真实验对改进后的DWA进行了验证。实验场景设置在一个18米×18米的区域内，与传统DWA相比，改进后的DWA在轨迹长度和出行时间方面显示出显著优势。具体来说，传统DWA机器人的轨迹长度为19.4米，所需时间为34.8秒，而改进后的DWA机器人的轨迹长度缩短至18.7米，时间减少至18.6秒。这一结果充分证明了改进后的DWA在优化人流控制方面的有效性。本研究提出的改进后的DWA不仅具有很强的科学合理性，而且在实际应用中也表现出了高效性。本研究对于提高城市公共场所的安全性和改善行人交通流状况具有重要的参考价值，并为未来人流控制技术的进一步发展提供了新的思路。
