Fleeting Decisions and Risks in Pedestrian Road-Crossing Behavior: Building Insight with Next-Generation Data, Models, and Platforms

行人过马路行为中的短暂决策和风险：利用下一代数据、模型和平台构建洞察力

• 批准号: 1729815
• 负责人: Paul Torrens
• 金额: $ 39.94万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1729815&HistoricalAwards=false
• 关键词: Fleeting; Decisions; Risks; Pedestrian; Road

In this project, the Principal Investigator will examine road-crossing behavior over very small moments of space and time, by observing and studying real-world road-crossing sites. The conditions observed will then be recreated in a motion capture studio that will allow collection of very detailed data that can be used to build what-if models for training, planning, and design. The decision to cross a road can take mere fractions of a second and centimeters of action, but over this small window of space and time, people are at risk of injury and death in collisions with vehicles. Despite decades of work to design interventions that might promote safe crossing behavior, many people continue to engage in unsafe crossing, among them our most vulnerable - pedestrian youth and seniors. The aim of the project is to uncover the, often cursory, decisions and risks that people invoke when they move at the roadside. The focus on the microcosm of road-crossing will enable identification and measurement of subtle signals from body language, expression, social cues in crowds, gaze behavior, and footfall that can convey both covert and overt insight into crossing intent. These signals and the road-crossing behaviors that they relate to will inform actionable understanding of road-crossing activities that can be used to improve the design of crossing infrastructure, that can be used in training and education, that might enhance signaling schemes, and that can be used to inform Advanced Driver Awareness Systems now being deployed in many vehicles.The project make use of a coupled research instrument that allows for coded real-world observation to be paired with advanced sensor-based instrumentation in motion capture studios, and with what-if modeling based on human automata that can facilitate the exploration, identification, and measurement of subtle signals of pedestrian decision-making and risk-taking while crossing. The technical focus of the project is to identify, capture, measure, and frame human-environment signals of road-crossing behavior in ways that can be used for broader pedestrian sensing and detection. The project will generate a robust library of data, including qualitative observations, sensor data, and model output that can be reused by communities in the socio-behavioral sciences and the computing sciences. These data, and the models they will power, will form the backbone of an immersive Virtual Geographic Environment that can be used for training and education.

在这个项目中，首席研究员将通过观察和研究现实世界的道路交叉口地点来检查在非常小的空间和时间瞬间内的道路交叉口行为。然后，观察到的条件将在动作捕捉工作室中重新创建，该工作室将允许收集非常详细的数据，这些数据可用于构建用于训练、规划和设计的假设模型。过马路的决定可能只需要几分之一秒和几厘米的行动，但在这个很小的空间和时间窗口内，人们面临着与车辆碰撞中受伤和死亡的风险。尽管几十年来致力于设计可能促进安全过马路行为的干预措施，但许多人仍然从事不安全过马路行为，其中包括我们最脆弱的人——行人青少年和老年人。该项目的目的是揭示人们在路边移动时通常做出的粗略决定和风险。对十字路口微观世界的关注将能够识别和测量来自肢体语言、表情、人群中的社交线索、凝视行为和脚步声的微妙信号，这些信号可以传达对十字路口意图的隐蔽和公开的洞察。这些信号和与之相关的过路行为将为对过路活动的可操作的理解提供信息，这些活动可用于改进过路基础设施的设计，可用于培训和教育，可能会增强信号方案，并且可用于为许多车辆中部署的高级驾驶员意识系统提供信息。该项目利用耦合研究仪器，允许将编码的现实世界观察与运动捕捉工作室中基于传感器的先进仪器配对，并与-if基于人体建模自动机可以促进行人决策和穿越时冒险的微妙信号的探索、识别和测量。该项目的技术重点是以可用于更广泛的行人感知和检测的方式识别、捕获、测量和构建道路穿越行为的人类环境信号。该项目将生成一个强大的数据库，包括定性观察、传感器数据和模型输出，可供社会行为科学和计算科学界重复使用。这些数据及其所支持的模型将构成可用于培训和教育的沉浸式虚拟地理环境的支柱。

项目成果

Data science for pedestrian and high street retailing as a framework for advancing urban informatics to individual scales

步行和商业街零售的数据科学作为将城市信息学提升到个体规模的框架

• DOI: 10.1007/s44212-022-00009-x
• 发表时间: 2022-10-03
• 期刊: Urban Informatics
• 作者: P. Torrens

Smart and Sentient Retail High Streets

智能且有感知的零售商业街

• DOI: 10.3390/smartcities5040085
• 发表时间: 2022-11-29
• 期刊: Smart Cities
• 影响因子: 6.4
• 作者: P. Torrens

Agent models of customer journeys on retail high streets

零售大街上客户旅程的代理模型

• DOI: 10.1007/s11403-022-00350-z
• 发表时间: 2022-05
• 期刊: Journal of Economic Interaction and Coordination
• 影响因子: 1.1
• 作者: Torrens; Paul M.
• 通讯作者: Paul M.

Geographic information science in the era of geospatial big data: A cyberspace perspective

地理空间大数据时代的地理信息科学：网络空间视角

• DOI: 10.1016/j.xinn.2022.100279
• 发表时间: 2022-07-01
• 期刊: The Innovation
• 作者: Xintao Liu;Min Chen;Christophe Claramunt;M. Batty;Mei‐Po Kwan;A. M. Senousi;Tao Cheng;J. Strobl;Cöltekin Arzu;John Wilson;T. B;rova;rova;M. Konečný;P. Torrens;Fengyuan Zhang;Li He;Jinfeng Wang;C. Ratti;O. Kolditz;A. Klippel;Songnian Li;Hui Lin;Guonian Lü
• 通讯作者: Guonian Lü

Modelling spatio-temporal patterns in pedestrian behavior at the edge with Jetson SOMs

使用 Jetson SOM 对边缘行人行为的时空模式进行建模

• 发表时间: 2019-11
• 期刊: November 4-6
• 作者: Torrens, Paul M.;Potdar, Kedar
• 通讯作者: Potdar, Kedar