2015/08/25 by Kardi Teknomo, Teknomo, Kardi, Gloria P. Gerilla +1
Computer Science · Engineering · Medicine · Physics and Astronomy · #Advertising #Astronomy #Automotive and Human Injury Biomechanics #Autonomous Vehicle Technology and Safety #Business #Computer graphics (images) #Computer science #Engineering #FOS: Computer and information sciences #FOS: Physical sciences #Hypermarket #Pedestrian #Physics #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Trajectory #Transport engineering #Vehicle Dynamics and Control Systems #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1508.06143
Proceedings of the Eastern Asia Society for Transportation Studies, Vol.7, 2009
arxiv created 2015/08/25 · openalex publication_date 2015/08/25 · arxiv updated 2015/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we propose a combination of pedestrian data collection and analysis and modeling that may yield higher competitive advantage in the business environment. The data collection is only based on simple inventory and questionnaire surveys on a hypermarket to obtain trajectory path of pedestrian movement. Though the data has limitation by using static trajectories, our techniques showed that it is possible to obtain aggregation of flow pattern and alley attractiveness similar to the result of aggregation using dynamic trajectory. A case study of a real hypermarket demonstrates that daily necessity products are closely related to higher flow pattern. Using the proposed method, we are also able to quantify pedestrian behavior that shoppers tend to walk about 7 times higher than the ideal shortest path