9:15 AM - 9:30 AM
[HTT17-07] Study on the Method to Evaluate Gradients in Walking Spaces
Keywords:Pedestrian space, Contour lines, Trajectory , Projection conversion
Introduction Currently, the number of foreign tourists in Japan is increasing due to the Covid-19 pandemic and weak yen. It is necessary to enhance the charm of Japanese cities and create a lively atmosphere. Tourist spots and the surrounding pedestrian spaces are becoming increasingly important. The Ministry of Land, Infrastructure, Transport and Tourism (MLIT) announced the “Roundtable on Urban Diversity and Innovation” on June 26, 2018. At this conference, the report, “Urban Renewal Starting with a Comfortable Town to Walk Around” was compiled. This program aims to shift from a car-centered to a human-focused city center, fostering innovation and enriching human-centered lifestyles. Purpose and Methods of the Research Greenery, including lawns, is utilized to create people-centered spaces. However, there are many problems in creating comfortable and walkable spaces. The goal of this study was to clarify the relationship between people's behavior and the structure of walking spaces. We believe that understanding this relationship can help in designing more walkable environments. The purpose of this study is to predict human behavior by focusing on the relationship between human behavior and gradient.
A video survey was conducted to investigate how gradients affect people's behavior. The survey was conducted at Maruyama Park, a tourist spot located in Kyoto City. Most of the gradients are gradual inclines, ranging from 3°to 6°. The park was selected because it attracts many pedestrians and is not affected by cars, allowing for the observation of unconscious behavior patterns.
The survey method consisted of multiple video recordings, each approximately 10 minutes long. We tracked multiple pedestrian trajectories at the confluence of five roads. Two reference points were selected using the Kyoto City Urban Planning Map and photographs of the trajectories. A reference square mesh was created and projection conversion of the trajectory photos was performed. The trajectory was traced on a flat surface to compare against the contour lines.
Looking at the same start-to-finish trajectory, the analysis showed that pedestrians followed similar trajectories regardless of time of day. The walking range remained consistent, with people walking perpendicular to the contour lines in a coherent movement pattern, while those walking along the contour lines were more spread out. We concluded that smaller differences in the angle relative to contour lines make it easier to walk.
Based on the results of the survey, we hypothesized that it might be possible to predict the movement of people using the contour lines. To test this, we selected a sidewalk along the Seta River in Otsu City, Shiga Prefecture, as the site for an experiment. A walking space unaffected by cars was a condition in the selection process. As in the initial survey, a mesh was drawn on the site and angles were calculated using contour lines. The angle differences between meshes were analyzed using contour lines through the mesh and video recordings were taken to confirm the validity of our evaluation.
Results showed that 33% of pedestrians followed predicted paths. Some pedestrians walked in areas with low predicted ratings. This suggests that not only contour lines but other factors may have influenced the results.
In conclusion, this study established a method to predict pedestrian movement based on gradients in walking spaces. Results indicate that the addition of other factors alongside contour line evaluations could improve the practicality and accuracy of pedestrian flow predictions.
A video survey was conducted to investigate how gradients affect people's behavior. The survey was conducted at Maruyama Park, a tourist spot located in Kyoto City. Most of the gradients are gradual inclines, ranging from 3°to 6°. The park was selected because it attracts many pedestrians and is not affected by cars, allowing for the observation of unconscious behavior patterns.
The survey method consisted of multiple video recordings, each approximately 10 minutes long. We tracked multiple pedestrian trajectories at the confluence of five roads. Two reference points were selected using the Kyoto City Urban Planning Map and photographs of the trajectories. A reference square mesh was created and projection conversion of the trajectory photos was performed. The trajectory was traced on a flat surface to compare against the contour lines.
Looking at the same start-to-finish trajectory, the analysis showed that pedestrians followed similar trajectories regardless of time of day. The walking range remained consistent, with people walking perpendicular to the contour lines in a coherent movement pattern, while those walking along the contour lines were more spread out. We concluded that smaller differences in the angle relative to contour lines make it easier to walk.
Based on the results of the survey, we hypothesized that it might be possible to predict the movement of people using the contour lines. To test this, we selected a sidewalk along the Seta River in Otsu City, Shiga Prefecture, as the site for an experiment. A walking space unaffected by cars was a condition in the selection process. As in the initial survey, a mesh was drawn on the site and angles were calculated using contour lines. The angle differences between meshes were analyzed using contour lines through the mesh and video recordings were taken to confirm the validity of our evaluation.
Results showed that 33% of pedestrians followed predicted paths. Some pedestrians walked in areas with low predicted ratings. This suggests that not only contour lines but other factors may have influenced the results.
In conclusion, this study established a method to predict pedestrian movement based on gradients in walking spaces. Results indicate that the addition of other factors alongside contour line evaluations could improve the practicality and accuracy of pedestrian flow predictions.