随着我国城市化进程的加快,城市人口继续增长,导致公共空间频繁拥挤,进而引发交通拥堵甚至安全事故。为了更有效地控制行人流量,提高公共空间的效率和安全性,本实验对传统的动态窗口法(DWA)进行了深入的研究和改进,并将其应用于行人流量的精细控制。具体来说,本研究全面回顾和分析了行人交通流的特点和传统DWA的工作原理。基于此,指出了传统DWA在处理复杂行人流场景方面的不足,并提出了有针对性的改进方案。这种改进方案的核心在于引入了新的评价函数,使DWA能够更准确地平衡决策过程中的各种因素,包括行人移动速度,方向,和空间分布。随后,通过仿真实验验证了改进的DWA。实验场景设置在18m*18m的区域内,与传统的DWA相比,改进的DWA在轨迹长度和行程时间上显示出显著的优势。具体来说,传统DWA机器人的轨迹长度为19.4m,所需时间为34.8s,改进的DWA机器人的轨迹长度缩短为18.7m,时间缩短至18.6s。该结果充分证明了改进的DWA在优化行人流量控制方面的有效性。本研究提出的改进DWA不仅具有很强的科学性,而且在实际应用中表现出很高的效率。本研究对提高城市公共空间的安全性,改善行人交通流状况具有重要的参考价值,为今后行人流量控制技术的进一步发展提供了新的思路。
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.