Automated data collection and analysis for pedestrian movement and behaviour

行人运动和行为的自动数据收集和分析

• 批准号: 561387-2020
• 负责人: Gales, JohnAdam
• 金额: $ 2.19万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=720127
• 关键词: Automated; data; collection; analysis; pedestrian

Current transportation infrastuture modelling which is required to ensure safety of pedestrians in normal and emergency conditions is based upon obsolete data sets and limited theoretical movement frameworks. This project attempts to establish a novel suite of datasets, tracking technology, and computational guidance to renew this discipline area. The objectives of the project are 1) Accurately represent population impeded and unimpeded movement density in MassMotion software; 2) Establish unique movement profiles and behavioral characteristics; 3) Establish a practitioners framework for optimizing circulation for transportation infrastructure (platforms, curbside, terminals, pedestrian villages); and 4) output and communicate results with relevant Accessibility Standards such as CAN/CSA B651 (Accessibility for the Built Environment) and CAN/CSA-B659 (Inclusive Design for an Aging Population).

目前的交通基础设施模型，需要确保行人在正常和紧急情况下的安全是基于过时的数据集和有限的理论运动框架。本计画尝试建立一套新颖的资料集、追踪技术与计算导引，以更新此一学科领域。该项目的目标是：1）在MassMotion软件中准确地表示人口受阻和畅通的运动密度; 2）建立独特的运动轮廓和行为特征; 3）建立优化交通基础设施流通的从业者框架（月台、路旁、总站、行人村）;以及4）输出并传达符合相关无障碍标准的结果，如CAN/CSA B651（建筑环境无障碍）和CAN/CSA-B659（老龄人口包容性设计）。